Job Board

To post new jobs:

Please submit the job post request through this link, and it will normally show up below within a week. If you have any questions, please contact the web chairs: Tianfan Xue (tianfan@google.com) or Tian Lan (tianlan@amazon.com).


Sr. Applied Scientist - Image Optimisation

Do you get excited about working on scientific problems that will have a large, significant and lasting impact for Amazon customers? Are you interested in Computer Vision and Machine Learning? Are you thrilled working in a startup-like environment? Search no more! We have an opening for a (Sr.) Applied Scientist in Berlin.

As a (Sr.) Applied Scientist, you will be driving projects and prototypes in the field of image optimisation/rendering for Amazon Retail Experiences. The team's scope includes but is not limited to: understanding perceptual image quality, optimising content (file standard compliant), thinking about novel Machine Learning inspired compression approaches and leveraging Computer Vision for content-aware image rendering (e.g., through image feature extraction).

Some of your key responsibilities include, but are not limited to:
· Build machine learning models (e.g., for image feature extraction)
· Develop optimisation strategies (e.g., for image optimisation)
· Collaborate with software development engineers to get scientific ideas into production quickly
· Join/lead scientific reading groups and engage with the scientific community (within Amazon and beyond)
· Think outside the box and identify novel opportunities for a better customer experience
More information on the team's past work and impact for Amazon Retail Experiences page can be found on the Amazon Blog: https://blog.aboutamazon.de/forschung-entwicklung/bildoptimierung-made-…

Your work will impact the shopping experience for millions of Amazon customers every day. Your ideas allow a fast path to production at scale and help us reshape the way we think about image rendering and delivery at Amazon.

BASIC QUALIFICATIONS
· PhD in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
· Peer reviewed scientific contributions in relevant field (e.g., CVPR, ICCV, ECCV, ICML, NeurIPS, ICLR)
· Experience in Python or C/C++
· Experience wich Machine Learning frameworks such as Tensorflow, MXNet or PyTorch
· Strong verbal and written communication skills

PREFERRED QUALIFICATIONS
· Expert knowledge of Computer Vision and/or Machine Learning, in particular: lower-level computer vision, signal processing, imaging and video standards, CNNs
· Experience applying theoretical models in an applied environment
· Industry experience (1+ yrs)

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build.

More info | Contact: Marie-Therese Festerling | Posted on: 2020-05-31

Computer Vision Applied Scientist

We are a computer vision research group in Berlin, Germany creating novel solutions in collaboration with product teams all across Amazon for some of the most visible and exciting problems out there. Our work sits right at the intersection of research and engineering and we are delivering products with real world impact in various application fields, e.g. for Prime Video, Prime Photos, Robotics and Retail. If that sounds interesting for you and if you would like to live in one of the most exciting places of the world, then we have the perfect role for you. We have open Applied Scientist positions for all levels of experience and this is what we are looking for:

Major Responsibilities:
· Research, design, implement and evaluate novel computer vision algorithms
· Work on large-scale datasets, creating scalable, robust and accurate computer vision systems in versatile application fields
· Collaborate closely with researchers and engineers to drive systems from prototyping to production level
· Collaborate with teams spread all around the world

If you thrive in a fast-paced environment, you’ll meet your match with us, as you will be part of a vibe of constant improvement. We don’t like to sit still, which is why we always treat every day like the first day. A day to make more good things happen for our customers. That's the kind of spirit that drives our success and you could be part of it. It’s as simple as this: Work Hard. Have Fun. Make History.

BASIC QUALIFICATIONS
- PhD in computer vision/machine learning or related experience
- Broad knowledge of fundamentals and state-of-the-art in computer vision/machine learning
- Coding skills in two or more programming languages such as Python, C, C++, Java etc.

PREFERRED QUALIFICATIONS
- Experience in publishing at major computer science conferences or journals
- Hands-on experience with popular deep learning frameworks such as MxNet and TensorFlow
- Hands-on experience with Python
- Strong verbal and written communication skills

Take a look at www.amazon.science to learn more about research highlights and publications from the Amazon science teams.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build.

More info | Contact: Marie-Therese Festerling | Posted on: 2020-05-31

Applied Science Manager

Customer Reviews, Deals and Content Moderation are community driven experiences that are key to the Amazon experience worldwide. Join the applied research team in Berlin, Germany supporting Community Shopping and driving the customer experience for these important programs.

The problems are real, with tangible customer impact. The work sits at the intersection of research and engineering, driving better quality in our reviews corpus, ensuring appropriate content across customer-submitted text, images and video at massive scale, and ensuring that the right deals surface for the right customer at the right time. The applications are wide and range from Generic ML to NLP and Computer Vision.

We are an applied research group in Berlin, Germany creating novel solutions in collaboration with product and engineering teams at the core of some of Amazon’s biggest and most engaged systems. If that sounds interesting for you and if you would like to live in one of the most exciting places of the world, then we have the perfect role for you. We have open Applied Scientist Manager position and this is what we are looking for:

Major Responsibilities
· Build and manage a team of 5-7 applied scientists
· Design, implement and evaluate ML models
· Work on large-scale datasets, creating scalable, robust and accurate ML based systems
· Collaborate closely with engineers to drive systems from prototyping to production level
· Collaborate with teams spread all around the world

BASIC QUALIFICATIONS
· PhD in machine learning or related experience
· Broad knowledge of fundamentals and state-of-the-art in machine learning
· Coding skills in one or more programming languages such as Python, Scala, Java, C, C++
· Proven track record of successful ML models and practical implementation

PREFERRED QUALIFICATIONS
· Hands-on experience with popular ML frameworks such as scikit-learn, MxNet or TensorFlow
· Strong verbal and written communication skills
· Experience with application development practices at scale
· Ability to work independently and in a team, understand business requirements and make the right trade-offs
· Familiarity with AWS services such as SageMaker is considered a plus

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build.

More info | Contact: Marie-Therese Festerling | Posted on: 2020-05-31

Applied Science Manager

Amazon's Intelligent Cloud Control Group in Berlin is looking for an Applied Science Manager to lead the research and development of large-scale machine learning implementations that will revolutionize the way Amazon operates the tens of thousands of software services and subcomponents across our retail businesses. With an ever-growing number of fleets, developers, customers, products, marketplaces, sellers, and businesses, the Amazon service graph is one of the largest and most complex tech ecosystems in the world. We are building an Intelligent Cloud Control system that enables Amazon businesses (Retail, Amazon Video, Kindle, and more) to accelerate innovation in the cloud.

As an Applied Science Manager in the Intelligent Cloud Control team, you'll leverage your own skills and those of your team of machine learning engineers, data scientists, and applied scientists to develop and evaluate machine learning models using extremely large datasets such as the orders, website traffic, telemetry, and logs from every host at Amazon. Our datasets extend into the multi-exabyte range, and our science products are of critical importance to the retail businesses of Amazon. You will own researching, developing, prioritizing, and releasing both prototypes and reliable automated production workflow for the model. You will collaborate with other managers and leaders to improve the Amazon retail customer experience.

Our responsibility is to maximize the availability and contribute to the better efficiency of Amazon’s retail experience, so our opportunities are endless. From natural language processing and information extraction of operational issues to unsupervised multi-variate anomaly detection to discover nodes of linked sub-system behavior, the insights and opportunities to discover and remediate customer-impacting issues are profound and our solutions worthy of publication.

We’re looking for engineers capable of using machine learning and other techniques to design, evaluate, and implement state-of-the-art solutions for never-before-solved problems.

BASIC QUALIFICATIONS
· A Master’s degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field; or equivalent combination of technical education and work experience.
· 4+ years of experience in Applied Machine Learning, Statistics, or a closely-related field.
· 1+ years of experience managing a software engineering or machine learning science team.
· Must have delivered features for at least one large-scale production system.

PREFERRED QUALIFICATIONS
· PhD in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field; or equivalent combination of technical education and work experience.
· 6+ years of experience in Applied Machine Learning, Statistics, or a closely-related field.
· 2+ years of experience managing a software engineering or machine learning science team.
· Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences.
· A proven track record of hiring and developing software engineers or machine learning scientists.
· A strong sense of curiosity and willingness to learn quickly, building knowledge and skills that this role requires.
· A deep understanding of the software development lifecycle, and a track record of shipping software on time.
· Experience with the Scrum methodology (or similar alternatives) for agile software development.
· Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
· Deep hands-on technical expertise in cloud-based distributed software design and development, especially utilizing AWS services.
· Knowledge of machine learning approaches and algorithms, and experience building complex highly-scalable systems that involve predictive models or applications of machine learning.
· Ability to handle multiple competing priorities in a fast-paced environment.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build.

More info | Contact: Marie-Therese Festerling | Posted on: 2020-05-31

Applied Scientist - Computer Vision

Customer Reviews, Deals and Content Moderation are community driven experiences that are key to the Amazon experience worldwide. Join the applied research team in Berlin, Germany supporting Community Shopping and driving the customer experience for these important programs.

The problems are real, with tangible customer impact. The work sits at the intersection of research and engineering, driving better quality in our reviews corpus, ensuring appropriate content across customer-submitted images and video at massive scale. You will partner closely with our engineering teams to develop novel algorithms, present your work to product and engineering teams at Amazon, publish scientific papers and apply for patents for your inventions.

We are an applied research group in Berlin, Germany creating novel solutions in collaboration with product and engineering teams at the core of some of Amazon’s biggest and most engaged systems. If that sounds interesting for you and if you would like to live in one of the most exciting places of the world, then we have the perfect role for you. We have open Applied Scientist positions for all levels of experience and this is what we are looking for:

Major Responsibilities:
· Design, implement and evaluate novel computer vision algorithms
· Work on large-scale datasets, creating scalable, robust and accurate computer vision systems
· Collaborate closely with engineers to drive systems from prototyping to production level
· Collaborate with teams spread all around the world

BASIC QUALIFICATIONS
· PhD in computer vision/machine learning or related experience
· Broad knowledge of fundamentals and state-of-the-art in computer vision/machine learning
· Coding skills in one or more programming languages such as Python, Scala, Java, C, C++
· Proven track record of successful models and practical implementation

PREFERRED QUALIFICATIONS
· Hands-on experience with popular ML frameworks such as MxNet or TensorFlow
· Strong verbal and written communication skills
· Experience with application development practices at scale, from problem definition to deployment.
· Ability to work independently and in a team, understand business requirements and make the right trade-offs
· Familiarity with AWS services such as SageMaker is considered a plus

More info | Contact: Marie-Therese Festerling | Posted on: 2020-05-31

Computer Vision Software Engineer

The Applied Research group within Intuitive Surgical has an immediate opening in Sunnyvale, CA for a research engineer with a focus on Computer Vision, Deep Learning and Software development, contributing to new technology development in the area of 3D scene understanding, spatial AI systems and surgical action recognition for next generation robotic surgery platforms. This role is an exciting opportunity to join a newly formed team and to contribute to its growth and it will give you an opportunity to test your knowledge in a challenging problem solving environment.

More info | Contact: Omid Mohareri | Posted on: 2020-05-31

Research Scientist, Mobile Manipulation Behaviors

At Toyota Research Institute (TRI), we’re working to build a future where everyone has the freedom to move, engage, and explore with a focus on reducing vehicle collisions, injuries, and fatalities. Join us in our mission to improve the quality of human life through advances in artificial intelligence, automated driving, robotics, and materials science. We’re dedicated to building a world of “mobility for all” where everyone, regardless of age or ability, can live in harmony with technology to enjoy a better life. Through innovations in AI, we’ll help…

- Develop vehicles incapable of causing a crash, regardless of the actions of the driver.
- Develop technology for vehicles and robots to help people enjoy new levels of independence, access, and mobility.
- Bring advanced mobility technology to market faster.
- Discover new materials that will make batteries and hydrogen fuel cells smaller, lighter, less expensive and more powerful.
- Develop human-centered AI systems to augment (not replace) human decision making to increase the quality of decisions (e.g. mitigate cognitive biases) and/or to facilitate faster innovation cycles.

Our work is guided by a dedication to safety – in both what we research and how we perform our research our goal is to benefit society. As a subsidiary of Toyota, TRI is fueled by a diverse and inclusive community of people who carry invaluable leadership, experience, and ideas from industry-leading companies. Over half of our technical team carries PhD degrees. We’re continually searching for the world’s best talent ‒ people who are ready to define the new world of mobility with us!

We strive to build a company that helps our people thrive, achieve work-life balance, and bring their best selves to work. At TRI, you will have the opportunity to enjoy the best of both worlds ‒ a fun environment with forward-thinking people who enjoy solving tough problems and the financial backing to successfully achieve our goals. Come work with TRI if you’re interested in transforming mobility through designing technology for safer cars, enabling the elderly to age in place, or designing alternative fuel sources. Start your impossible with us.

TRI is assembling a world-class team to develop and integrate innovative solutions that enable a robot to perform complex, human-level mobile manipulation tasks, navigate with and among people, and learn and adapt over time. The team will develop, deploy, and validate systems in real-world environments, in and around homes.

The team will be focused on heavily leveraging machine learning to marry perception, prediction, and action to produce robust, reactive, coordinated robot behaviors, bootstrapping from simulation, leveraging large amounts of data, and adapting in real world scenarios.

TRI has the runway, roadmap, and expertise to transition the technology development to a product that impacts the lives of millions of people. Apply to join a fast moving team that demands high-risk innovation and learning from failures, using rigorous processes to identify key technologies, develop a robust, high quality system, and quantitatively evaluate performance. As part of the team, you will be surrounded and supported by the significant core ML, cloud, software, and hardware expertise at TRI, and be a part of TRI's positive and diverse culture.

Responsibilities 
* Develop, integrate, and deploy algorithms linking perception to autonomous robot actions, including manipulation, navigation, and human-robot interaction

* Invent and deploy innovative solutions at the intersection of machine learning, mobility, manipulation, human interaction, and simulation for performing useful, human-level tasks, in and around homes

* Invent novel ways to engineer and learn robust, real-world behaviors, including using optimization, planning, reactive control, self-supervision, active learning, learning from demonstration, simulation and transfer learning, and real-world adaptation

* Be part of a team that fields systems, performs failure analysis, and iterates on improving performance and capabilities

* Follow software practices that produce maintainable code, including automated testing, continuous integration, code style conformity, and code review

Qualifications:
* M.S. or Ph.D. in an engineering related field

* A strong track record in inventing and deploying innovative autonomous behaviors for robotic systems in real-world environments

* Expertise and experience in areas such as reactive control, trajectory optimization, coordinated whole-body control, dexterous manipulation, arm motion planning, grasp planning, navigation, and human interaction

* Expertise and experience in applying machine learning to robotics, including areas such as reinforcement, imitation, and transfer learning

* Strong software engineering skills, preferably in C++, and analysis and debugging of autonomous robotic systems

* A team player with strong communication skills, and a willingness to learn from others and contribute back to the robotics community with publications or open source code

* Passionate about seeing robotics have a real-world, large-scale impact

More info | Contact: Janet Bourland | Posted on: 2020-05-31

Research Scientist, Mobile Manipulation Perception

At Toyota Research Institute (TRI), we’re working to build a future where everyone has the freedom to move, engage, and explore with a focus on reducing vehicle collisions, injuries, and fatalities. Join us in our mission to improve the quality of human life through advances in artificial intelligence, automated driving, robotics, and materials science. We’re dedicated to building a world of “mobility for all” where everyone, regardless of age or ability, can live in harmony with technology to enjoy a better life. Through innovations in AI, we’ll help…

- Develop vehicles incapable of causing a crash, regardless of the actions of the driver.
- Develop technology for vehicles and robots to help people enjoy new levels of independence, access, and mobility.
- Bring advanced mobility technology to market faster.
- Discover new materials that will make batteries and hydrogen fuel cells smaller, lighter, less expensive and more powerful.
- Develop human-centered AI systems to augment (not replace) human decision making to increase the quality of decisions (e.g. mitigate cognitive biases) and/or to facilitate faster innovation cycles.

Our work is guided by a dedication to safety – in both what we research and how we perform our research our goal is to benefit society. As a subsidiary of Toyota, TRI is fueled by a diverse and inclusive community of people who carry invaluable leadership, experience, and ideas from industry-leading companies. Over half of our technical team carries PhD degrees. We’re continually searching for the world’s best talent ‒ people who are ready to define the new world of mobility with us!

We strive to build a company that helps our people thrive, achieve work-life balance, and bring their best selves to work. At TRI, you will have the opportunity to enjoy the best of both worlds ‒ a fun environment with forward-thinking people who enjoy solving tough problems and the financial backing to successfully achieve our goals. Come work with TRI if you’re interested in transforming mobility through designing technology for safer cars, enabling the elderly to age in place, or designing alternative fuel sources. Start your impossible with us.

TRI is assembling a world-class team to develop and integrate innovative solutions that enable a robot to perform complex, human-level mobile manipulation tasks, navigate with and among people, and learn and adapt over time. The team will develop, deploy, and validate systems in real-world environments, in and around homes.

The team will be focused on heavily leveraging machine learning to marry perception, prediction, and action to produce robust, reactive, coordinated robot behaviors, bootstrapping from simulation, leveraging large amounts of data, and adapting in real world scenarios.

TRI has the runway, roadmap, and expertise to transition the technology development to a product that impacts the lives of millions of people. Apply to join a fast moving team that demands high-risk innovation and learning from failures, using rigorous processes to identify key technologies, develop a robust, high quality system, and quantitatively evaluate performance. As part of the team, you will be surrounded and supported by the significant core ML, cloud, software, and hardware expertise at TRI, and be a part of TRI's positive and diverse culture.

Responsibilities
Develop, integrate, and deploy algorithms linking perception to autonomous robot actions, including manipulation, navigation, and human-robot interaction
Invent and deploy innovative solutions at the intersection of machine learning, computer vision, multi-sensor perception, and simulation for understanding human environments and humans, in and around homes
Invent novel ways to create, label, and use large, possibly distributed datasets, using self-supervision, active learning, simulation, and real-world adaptation
Be part of a team that fields systems, performs failure analysis, and iterates on improving performance and capabilities
Follow software practices that produce maintainable code, including automated testing, continuous integration, code style conformity, and code review

Qualifications
M.S. or Ph.D. in an engineering related field
A strong track record in inventing and deploying innovative perception algorithms to robotic systems in real-world environments
Expertise and experience in areas such as object detection, classification, segmentation, and tracking, sensor fusion, state estimation, local 3d mapping and reconstruction, person detection, and human pose estimation
Expertise and experience in applying deep learning to perception problems
Strong software engineering skills, preferably in C++, and analysis and debugging of robotic perception algorithms
A team player with strong communication skills, and a willingness to learn from others and contribute back to the robotics community with publications or open source code
Passionate about seeing robotics have a real-world, large-scale impact

More info | Contact: Janet Bourland | Posted on: 2020-05-31

Research Scientist - Computer Vision

We are looking for computer vision and machine learning researchers to develop methods for video understanding and autonomous learning for next generation AI systems. Research topics include visual video understanding; cross-modal learning from visual, textual and audio inputs; incremental and few-shot learning; and self- and weakly-supervised learning. Particular emphasis is given to multi-modal video understanding, where the goal is to automatically generate a description of a long video (e.g., movie, Youtube video, news report) based on multiple modalities, such as video, speech and non-vocal audio.

Applicants should have a PhD degree in computer science or applied mathematics (or equivalent practical experience); experience in computer vision, machine learning, deep learning; a strong publication record; programming experience in C/C++, python, tensorflow.

More info | Contact: Cordelia Schmid | Posted on: 2020-05-31

Software Engineer - Machine Learning and Algorithms

ABOUT US
Moqi was founded under the belief that true AI innovations come from breakthroughs of the very fundamental level. Our mission is to uncover the fundamental principles of intelligence. We believe that AI devised in this way will ultimately soar past un-enhanced human thinking. The purpose of this endeavor is not to displace us but to amplify our cognitive abilities and ultimately expand the reach of what is already a human-machine civilization.
This is surely a long-term goal, but our world-class researchers and engineers are making exciting progress. By implementing our research in the application of fingerprint recognition, we were able to create the world's first fully automated large-scale fingerprint identification system, matching complex low-quality fingerprints against billion-scale fingerprint database in real time.

Responsibilities
* Participate in research of next-generation large scale image searching technologies and machine learning solutions.
* Develop solutions for real-world and billion scale applications

Qualifications
Minimum qualifications
* MS degree in Computer Science or related technical field or equivalent practical experience.
* Experience with one or more general purpose programming languages including but not limited to: Python, C/C++, or Go.
* Experience in Machine Learning.
* Knowledge in Algorithms and Data Structures.
* Contribution to research and open source community.
* Excellent analytical and problem solving skills.
* Fluent English.
Preferred qualifications
* PhD in Computer Science, Engineering or other related technical field.
* Experience with deep learning, familiar with TensorFlow/Pytorch/MXNet, etc.
* Strong publication record on machine learning, data mining, etc.
* Proven record of developing truly original research or solutions.
* Experience in Computer Vision, NLP applications.
* Large data analysis and visualization experience.

You can learn more from : https://fingerid.ai/

More info | Contact: Sarah Qi | Posted on: 2020-05-27

Research Engineer - Computer Vision

ABOUT US
Moqi was founded under the belief that true AI innovations come from breakthroughs of the very fundamental level. Our mission is to uncover the fundamental principles of intelligence. We believe that AI devised in this way will ultimately soar past un-enhanced human thinking. The purpose of this endeavor is not to displace us but to amplify our cognitive abilities and ultimately expand the reach of what is already a human-machine civilization.
This is surely a long-term goal, but our world-class researchers and engineers are making exciting progress.
By implementing our research in the application of fingerprint recognition, we were able to create the world's first fully automated large-scale fingerprint identification system, matching complex low-quality fingerprints against billion-scale fingerprint database in real time.

Responsibilities
* Participate in research of next-generation large scale image searching technologies and machine learning solutions.
* Develop solutions for real-world and billion scale applications

Qualifications
Minimum qualifications
* MS degree in Mathematics, Computer Science or related technical field or equivalent practical experience.
* Experience with one or more general purpose programming languages including but not limited to: C/C++ Python, or Go.
* Knowledge with Calculus, Linear Algebra, Probability.
* Knowledge in Algorithms and Data Structures.
* Experience in Machine Learning.
* Experience in Computer Vision applications.
* Contribution to research communities and/or efforts, including publishing papers at conferences such as CVPR, ICCV, NIPS, ICML,KDD, etc.
* Fluent English.
Preferred qualifications
* PhD in Mathematics, Computer Science, Engineering or other related technical field.
* Strong Computer System experience.
* Large Data Analysis and visualization experience.
* Strong publication record.
* Exposure in Deep Learning, and neural networks for computer vision tasks.
* Proven record of developing truly original research or solutions.
* Experience with stereo vision, structured light or photometrics.
* Strong knowledge in Numerical Algorithms.
* Strong knowledge in Computational Geometry and Computer Graphics.
* GPU programming experience.
* Excellent problem-solving and analytical skills.

You can learn more from : https://fingerid.ai/

More info | Contact: Sarah Qi | Posted on: 2020-05-27

Research Engineer - Computer Vision

ABOUT US
Moqi was founded under the belief that true AI innovations come from breakthroughs of the very fundamental level. Our mission is to uncover the fundamental principles of intelligence. We believe that AI devised in this way will ultimately soar past un-enhanced human thinking. The purpose of this endeavor is not to displace us but to amplify our cognitive abilities and ultimately expand the reach of what is already a human-machine civilization.
This is surely a long-term goal, but our world-class researchers and engineers are making exciting progress.
By implementing our research in the application of fingerprint recognition, we were able to create the world's first fully automated large-scale fingerprint identification system, matching complex low-quality fingerprints against billion-scale fingerprint database in real time.

Responsibilities
* Participate in research of next-generation large scale image searching technologies and machine learning solutions.
* Develop solutions for real-world and billion scale applications

Qualifications
Minimum qualifications
* MS degree in Mathematics, Computer Science or related technical field or equivalent practical experience.
* Experience with one or more general purpose programming languages including but not limited to: C/C++ Python, or Go.
* Knowledge with Calculus, Linear Algebra, Probability.
* Knowledge in Algorithms and Data Structures.
* Experience in Machine Learning.
* Experience in Computer Vision applications.
* Contribution to research communities and/or efforts, including publishing papers at conferences such as CVPR, ICCV, NIPS, ICML,KDD, etc.
* Fluent English.
Preferred qualifications
* PhD in Mathematics, Computer Science, Engineering or other related technical field.
* Strong Computer System experience.
* Large Data Analysis and visualization experience.
* Strong publication record.
* Exposure in Deep Learning, and neural networks for computer vision tasks.
* Proven record of developing truly original research or solutions.
* Experience with stereo vision, structured light or photometrics.
* Strong knowledge in Numerical Algorithms.
* Strong knowledge in Computational Geometry and Computer Graphics.
* GPU programming experience.
* Excellent problem-solving and analytical skills.

You can learn more from : https://fingerid.ai/

More info | Contact: Sarah Qi | Posted on: 2020-05-27

Research Scientist (Machine Learning / Remote Sensing Data Assimilation)

Cloud to Street is the leading flood mapping platform designed to protect the world’s most climate-vulnerable communities. By harnessing global satellites, advanced science, and community intelligence, we monitor worldwide floods in near real-time and remotely analyze local flood exposure at a click of a button. Our mission is to ensure that all vulnerable governments finally access the high quality information they need to prepare for and respond to increasing catastrophes. Founded by two women at Yale and seeded by Google, Cloud to Street is or has been used by governments across 15 countries. We are on track to enable new flood protection and insurance for 10 million people in the next 5 years.

We are looking for a best-in-class data fusion scientist to lead innovation to downscale passive microwave sensors using radar and optical high resolution flood maps. You should apply if you are eager to use science to reduce the impact of catastrophic flooding and build an innovative and sustainable organization. In this role, you will lead the development of machine learning based algorithms trained on high resolution flood events to downscale passive microwave sensors. You will work with a team of scientists and engineers with expertise in remote sensing (optical, radar, and passive microwave), hydrology, climate, social vulnerability, UX, and machine learning to i) optimize and improve Cloud to Street’s current flood mapping system and ii) build the next generation of tools to ensure financial protection from floods in marginalized communities

Primary Responsibilities
- Develop new and incorporate existing flood detection methods at the forefront of science and technology
- Improve Cloud to Street’s existing algorithms to extract data from passive microwave satellites and other sensors
- Design and manage product development pipelines in response to needs from governments, aid agencies, and insurers
- Collaborate with a team of exceptional scientists and engineers that want you to grow and be successful
- You tell us! Each member has skills not in their job description that are important for our growth. We would love to hear your unique talents and how we can help each other grow.

Characteristics of a Successful Candidate
- Master’s or PhD in geography, earth science, atmospheric science, engineering, computer science, or a related field with a focus on remote sensing and/or geospatial analysis
- Scientifically sound approach to machine learning enabled data fusion, especially with computer vision techniques
- Code proficiency in python
- Self-starter with ability to work within a fast-paced and rapid-evolving startup
- Eagerness to learn new skills and help with the task at hand
Commitment to justice, diversity, science, and solidarity with vulnerable communities

Useful Experience
- Coding proficiency using Google Earth Engine JavaScript and/or Python APIs, and/or open source geospatial Python packages
- Experience using machine learning to develop products or in industry
- Experience downscaling coarse resolution satellite imagery
- Experience with data fusion or data assimilation with satellite imagery, especially using random forests or convolutional neural networks
- Understanding of hydrology and physically-based flood models
- Contributing to a shared codebase on GitHub with multiple collaborators
- Using virtual machines on Google Cloud or similar platform
Working in disaster relief or in low or middle-income countries

As a Cloud to Street member, you:
- Lead development of rigorous science at start-up technology company focused on social impact and represent our organization at scientific and development meetings
- Serve the underserved by reducing the scientific barriers for low and middle income countries to access the information governments, businesses, and communities need to sustainably develop and thrive
- Are in solidarity with vulnerable communities by spending time with flood affected populations and organizations who serve them
- Increase equity by making information accessible to historically marginalized communities and building a diverse and inclusive start-up

To Apply
Applicants are requested to send their submissions to hiring@cloudtostreet.info with:
- Subject line: Research Scientist (Machine Learning and Remote Sensing Data Assimilation), Cloud to Street
- Attached CV/resume
- Relevant publications or past projects
- Paragraph expressing interest

Applications will be accepted until the position is filled with the intent to start the right candidate as soon as possible.

Cloud to Street is devoted to building an inclusive and diverse company. Women, people of color, and individuals with disabilities are especially encouraged to apply.

More info | Contact: Maddy Ryan | Posted on: 2020-05-27

Fully funded PhD studentship | 3D human pose estimation and shape reconstruction for biomechanics

Applications are invited for an exciting fully-funded PhD studentship at the Faculty of Engineering, the University of Nottingham.

Research area. The research topic focuses on developing computer vision and machine learning based solutions that enable in-natura markerless motion capture for biomechanical modelling in Biomedical and Sports Engineering. Specifically, it addresses the fundamental research problem of reconstruction of person-specific human pose, kinematics, and surface geometry to enhance our understanding of the non-linear behaviour of human motion, musculoskeletal injury and disease and enable modelling of soft-tissue dynamics and human-object interaction.

The project. The candidate is expected to develop a fast and robust method for inferring and tracking 3D human pose and surface geometry. The method will be mainly based on visual sensing complemented by Inertial and force sensors. The method can use either or both of model-based and learning-based approaches, such as CNN based segmentation, geometric CNNs, or convolutional kernel filter based tracking. The candidate will have access to a newly established state-of-the-art motion capture laboratory.

The candidate. The ideal candidate will have;

a first or upper second class honours or Masters degree in Electrical and Electronic Engineering, Physics, Computer Science, or other relevant and equivalent degree from a quality recognised institution.
a solid background in mathematics and excellent analytical and numerical skills, as well as problem solving skills
strong background in 3D computer vision, pose estimation, shape reconstruction, structure from motion, segmentation, or object detection.
experience in image or video processing and digital signal processing.
strong programming skills in Matlab, C/C++, or Python. Previous hands-on experience with deep learning platforms and agile software development as well as experience of working within industry will be an advantage.
very good written and communication skills and fluency in English.
a driven, independent professional and self-reliant work attitude within a fast-paced & collaborative environment.

The offer. The scholarship on offer (to eligible students) is for a minimum of three years and includes a tax-free stipend of 15,285 per year (for 2020/21) and tuition fees. It is available to students of UK and EU nationality. Applicants must obtain the support of the potential supervisor prior to submitting their application.

Informal enquiries about the project may be addressed to Dr Ami Drory. Please (i) insert your cover letter, CV, copies of academic transcripts, a list of publications, and contact details for two academic referees into a single pdf file. (ii) Name the file with your name as ”firstName_lastName_phd”. (iii) e-mail to: Ami.Drory [ at ] nottingham.ac.uk, with [3D shape reconstruction PhD application - lastName] as the email subject. Applications without academic transcripts or academic referees will not be considered. Applicants are advised to include copies of any publications or examples of their technical writing, such as code projects, project report or dissertation in support of the application.

Application instructions. With the support of the potential supervisor, formal applications are to be made via http://www.nottingham.ac.uk/pgstudy/apply/applyonline.aspx.

Closing date for applications. Review of applications will commence on 1 August 2020 and remain open until filled. A start date is expected to be as soon as practical thereafter.

More info | Contact: Ami Drory | Posted on: 2020-05-27

Event-based Vision - Ph.D. Position at TU-Berlin

We seek a PhD candidate to investigate novel techniques in the exciting field of event cameras. The goal is to combine model-based and deep learning methods for scene understanding with these revolutionary visual sensors.
Our research: https://sites.google.com/view/guillermogallego/research/event-based-vis…

Your profile:
- Successfully completed university degree (Master, Diplom or equivalent) in Computer Science or a related engineering subject with outstanding results.
- Excellent knowledge of and experience with computer vision, machine learning, object-oriented programming and applied mathematics.
- Excellent written and spoken English skills; willingness to learn German is expected.

How to apply? Send by e-mail to guillermo.gallego@tu-berlin.de (EECS Department):
- Cover Letter with your interest and experience related to the position (1 page).
- CV. Please indicate your relevant skills, scientific publications, awards, research videos and/or code, professional profile(s).
- Bachelor’s and Master's degrees and transcripts. Specify your GPA (e.g. 3.8/4.0)

Salary: Research Assistant – grade E 13 TV-L Berliner Hochschulen
To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired.

More info | Contact: Guillermo Gallego | Posted on: 2020-05-27

PhD in Perception and Forecasting, Computer Vision and Machine Learning

The newly founded Perception and Intelligence Lab (PINLab) is seeking exceptional and highly-motivated full-time Ph.D. students to research on one or a combination of these topics:
- Forecasting the future motion of people, vehicles and other objects
- Detection, recognition and re-identification with RGB and novel event-cameras
- Learning to learn (meta learning) and to generalize (domain adaptation)

The research work would leverage and define novel state-of-the-art models based on Deep Neural Networks and Spike Neural Networks, addressing the network memory, learning, reasoning and adaptation capabilities.
Initial work would stand on most recent achievements from our team, published at the TOP conference (CVPR) and journal (TPAMI) in the field:
- B Munjal, S Amin, F Tombari, F Galasso. Query-guided End-to-End Person Search. CVPR'19. (https://arxiv.org/abs/1905.01203)
- I Hasan, F Setti, T Tsesmelis, V Belagiannis, S Amin, A Del Bue, M Cristani, F Galasso. Forecasting People Trajectories and Head Poses by Jointly Reasoning on Tracklets and Vislets. TPAMI'19 (https://arxiv.org/abs/1901.02000)
- I Hasan, F Setti, T Tsesmelis, A Del Bue, F Galasso, M Cristani. MX-LSTM: mixing tracklets and vislets to jointly forecast trajectories and head poses. CVPR'18 (https://arxiv.org/abs/1805.00652)

The PhD student would collaborate with scientists at the Dept. of Computer Science at Sapienza (https://www.di.uniroma1.it/en), a department of Excellence in Italy: #1 in Computer Science and in the top 1% among all other Italian departments. The student would be given the opportunity to collaborate with international academic partners and companies, to experience research and innovation transfer.

We provide equal opportunities to all applicants and favour diversity. Any expertise or prior knowledge in computer vision and machine learning is welcome. Prior publication at international conferences is an advantage. Ability to program in Python/C/C++ is desirable, as well as prior experience with Pytorch and TensorFlow. Other programming languages, communication skills and team play will also be welcome.

Submit your expression of interest by 12 June 2020
Direct your submission to Prof. Fabio Galasso (galasso@di.uniroma1.it), head of the PINLab.
Include your CV, cover letter, publication list and contact details of 2 referees.

Eligibility: a Master’s degree is a pre-requisite for the Ph.D.

More info | Contact: Prof. Fabio Galasso | Posted on: 2020-05-27

Artificial Intelligence/Machine Learning Research Scientist

Cloud to Street is the leading flood mapping platform designed to protect the world’s most climate-vulnerable communities. By harnessing global satellites, advanced science, and community intelligence, we monitor worldwide floods in near real-time and remotely analyze local flood exposure at a click of a button. Our mission is to ensure that all vulnerable governments finally access the high quality information they need to prepare for and respond to increasing catastrophes. Founded by two women at Yale and seeded by Google, Cloud to Street is or has been used by governments across 15 countries. We are on track to enable new flood protection and insurance for 10 million people in the next 5 years.

We are looking for a best-in-class Artificial Intelligence/Machine Learning Research Scientist to build tools for turning satellite data into actionable insights. You should apply if you are eager to develop scalable approaches to reducing the impact of catastrophic flooding and if you are excited to build an innovative and sustainable organization. In this role, you will take ownership of Cloud to Street’s machine learning and data science efforts. You will be building the full pipeline from data collection and creation to model testing and benchmarking. You will work with a team of scientists and engineers with expertise in remote sensing (optical and radar), hydrology, climate, social vulnerability, UX, and machine learning to turn petabytes of satellite data into meaningful information to empower the world’s most vulnerable communities.

Primary Responsibilities
Design ML-based solutions to problems facing the company, including but not limited to:
- Flood detection
- Cloud detection
- Gap filling (physically based inpainting)
- Present findings in an accessible way to science and product teams
Integrate successful experiments and algorithms into C2S product
- Work with with a team including a machine learning data fusion specialist, data engineer, the Chief Science Officer, Technology director and help grow the machine learning and data engineering team
- Utilize Google Earth Engine and the Google Cloud Platform tools to run algorithms and develop models
- Visualize and explain work through presentations and notebooks

Characteristics of a Successful Candidate
- MSc or PhD in computer science, a related field, or equivalent experience
- Demonstrated ability to distill data into algorithms and results
- Experience developing and deploying deep learning algorithms
- Experience with a variety of machine learning techniques
- Excited to tackle difficult research questions
-Passion for developing technology to serve the most vulnerable

Useful Experience
- Coding proficiency using Google Earth Engine JavaScript and/or Python APIs, and/or open source geospatial Python packages
- Experience using machine learning to develop products or in industry
- Experience with computer vision with imagery, especially with satellite imagery or using convolutional neural networks
- Contributing to a shared codebase on GitHub with multiple collaborators
- Using virtual machines on Google Cloud or similar platform
- Working in disaster relief or in low or middle-income countries

As a Cloud to Street team member, you:
- Lead development of rigorous science at start-up technology company focused on social impact and represent our organization at scientific and development meetings
- Serve the underserved by reducing the scientific barriers for low and middle income countries to access the information governments, businesses, and communities need to sustainably develop and thrive
- Are in solidarity with vulnerable communities by spending time with flood affected populations and organizations who serve them
Increase equity by making information accessible to historically marginalized communities and building a diverse and inclusive start-up

To Apply
Applicants are requested to send their submissions to hiring@cloudtostreet.info with:
- Subject line: AI/ML Research Scientist, Cloud to Street
- Attached CV/resume
- Relevant publications or past projects
- Paragraph expressing interest

More info | Contact: Bessie Schwarz | Posted on: 2020-05-27

10 PhD positions – Applied Artificial Intelligence Institute, Australia

The Applied Artificial Intelligence Institute (A2I2) at Deakin University has PhD scholarships available for both local and international students. The institute is a top Australian research body focusing on Human-centred AI, with world-class research facilities. The scholarships provide an opportunity to join a large and diverse group of students, and work with world-class researchers on some of the most exciting AI problems.

We are looking for motivated candidates who are available to join any time between June 2020 and May 2021.

Students will be supervised by senior members of the A2I2, including ARC Laureate Fellow, Alfred Deakin Professor Svetha Venkatesh, and supported by experienced postdocs. A2I2 researchers consistently publish in top international AI conferences (NeurIPS, ICML, ICLR, AAAI, IJCAI, CVPR). Our graduates and post-docs go on to good positions at some of the highest profile institutions and companies.

Students have the potential to be part of a large team working towards a wide range of AI frontiers, including but not limited to:

(1) AI Fundamentals
o Reinforcement learning
o Deep learning 2.0
o Computer vision
o Algorithmic assurance
o Multi-agent systems
o Value alignment
(2) AI Applications
o Healthcare
o Structural biology
o Material sciences
o Accelerating discovery
o Smart homes
o Cybersecurity
o Software automation
(3) AI Software Engineering
o Improving engineering productivity
o Competency-aware AI
o Engineering methodologies, management, and governance.

A2I2 offers full tuition + stipend scholarships available (the 2020 annual stipend rate is $28,092 tax-free), as well as top up scholarships for those who have already received other funding. Each scholarship also includes attractive HDR funding to cover the cost of presenting at the major international conferences in the field and research facilities to support student’s candidature. Scholarship holders can claim up to $1,500 for relocation expenses.

We welcome applications at any time. Please submit your application as soon as possible.

For more information please contact HDR support coordinator, Dr Trang Tran at trang.tran@deakin.edu.au

Brief projects outline is available here: https://bit.ly/3g9RriC

A full description of our PhD program is available here: https://bit.ly/2TjOxOs

More info | Contact: Dr Trang Tran | Posted on: 2020-05-27

Postdoctoral Fellowship Position for AutoML / Bayesian Optimization / Algorithm Configuration

Your Profile
● Ph.D. in statistics, machine learning, biostatistics, computer science or a related
quantitative field
● Excellent knowledge of machine learning and statistics
● Strong programming skills (R or Python or C++) and optimally experience in working with high-performance computation clusters for benchmarking
● Excellent academic publication track record in relevant machine learning journals and conferences
● Strong communication and interpersonal skills, professional and confident
communication with industrial partners is a strong plus
● Strong interest in Automated Machine Learning, Algorithm Configuration, Meta
Learning and Bayesian Optimization
● Eagerness to support and supervise a team of highly motivated Ph.D. and graduate students, first experiences in team leadership is a plus
● Fluency in written and spoken English

What we provide
● Excellent academic environment and a team that is both highly skilled and highly
motivated
● Personal contact with industry partners that apply machine learning in practice via the ADA Lovelace Center
● Life and work in Munich, Germany’s most vibrant city with a very active machine and deep learning community
● Access to state of the art high-performance computing clusters within LMU as well as Fraunhofer IIS

How to apply
● A short statement letter promoting you as the ideal candidate for the position (~1 page)
● A detailed CV, with special focus on: obtained degrees, taken classes in relevant
topics, publications, programming skills and projects, track record

More info | Contact: Dr. Juliane Lauks | Posted on: 2020-05-18

Postdoctoral Fellowship Position for AutoML / Bayesian Optimization / Algorithm Configuration

Your Profile
● Ph.D. in statistics, machine learning, biostatistics, computer science or a related
quantitative field
● Excellent knowledge of machine learning and statistics
● Strong programming skills (R or Python or C++) and optimally experience in working
with high-performance computation clusters for benchmarking
● Excellent academic publication track record in relevant machine learning journals and conferences
● Strong communication and interpersonal skills, professional and confident
communication with industrial partners is a strong plus
● Strong interest in Automated Machine Learning, Algorithm Configuration, Meta
Learning and Bayesian Optimization
● Eagerness to support and supervise a team of highly motivated Ph.D. and graduate students, first experiences in team leadership is a plus
● Fluency in written and spoken English

What we provide
● Excellent academic environment and a team that is both highly skilled and highly
motivated
● Personal contact with industry partners that apply machine learning in practice via the ADA Lovelace Center
● Life and work in Munich, Germany’s most vibrant city with a very active machine and deep learning community
● Access to state of the art high-performance computing clusters within LMU as well as Fraunhofer IIS

How to apply
● A short statement letter promoting you as the ideal candidate for the position (~1 page)
● A detailed CV, with special focus on obtained degrees, taken classes in relevant
topics, publications, programming skills and projects, track record
Interested applicants should send the necessary documents in a single PDF

document via email to: tieubinh.ly@stat.uni-muenchen.de (Tieu-Binh Ly) quoting “Postdoc Application, ADA Lovelace Center” in the email subject line.

More info | Contact: Tieu-Binh Ly | Posted on: 2020-05-18

Applied Research Scientist - CV, NLP and ML

About Us
There are products that customers think are cool at the moment, and then there are products that customers cannot live without because they are so incredibly useful. At Matician, we are building the latter because these are the products worth spending our lives on. We want to build great products to solve real problems.

We believe that sensors and algorithms are finally good enough to reimagine home devices and apply Level 5 autonomy and mobility so that people can save time and energy bypassing repetitive and mundane tasks inside the home.

We're a small team with a singular focus on product that combines technologies such as vision, ML, structure-from-motion, and robotics. Our goal is to ship products that people love.

About the Program
Our Applied Research Scientist position is a product-focused-research position where you will research, apply, and optimize machine learning, computer vision, natural language and perception algorithms for autonomous robots. You’ll play an integral role, not just in researching algorithms, but also in product development, patents and other aspects of building a company from the ground up. Unlike other programs that focus just on conducting research and publication, our program places heavy emphasis on the process of refining and engineering the research into a product that people can buy.

We’d love to hear from you if:

You are genuinely motivated to help those around you, including users at various levels of experience.

You are passionate about tackling large complex projects and are adaptable to learning outside your normal comfort zones.

You love diagnosing complex technical issues and providing hands-on support for software to hardware solutions.

Your curiosity to learn and grow is inversely proportional to your level of ego.

You are excited to do great work.

Responsibilities
Collaborate with the HW, SW, and Algorithms team to bring product vision to life
Everything involved in applying an ML model to a production use case
Designing and coding up the neural network, gathering and refining data, training and tuning the model
Deploying it at scale with high throughput and uptime
Analyzing the results in order to continuously update and improve accuracy and speed

Qualifications
PhD/MS in Computer science, Machine Learning, AI or Related technical field
Experience applying theoretical models in an applied environment
Ability to solve problems and identify areas of improvement
Ability to write clean, reliable code that can be easily maintained
Experience with Python, with experience in Tensorflow, PyTorch or Numpy a plus
Experience with working on computer vision, machine learning or NLP problems
Familiarity with modern Deep Learning algorithms
Excellent verbal and written communication skills
Comfortable with running and interpreting common statistical tests and with common data science/learning techniques
Ability to work in a fast-paced, autonomously driven, and demanding start-up atmosphere

More info | Contact: Josh Kapla | Posted on: 2020-05-18

A.I. Residency

About Us
There are products that customers think are cool at the moment, and then there are products that customers cannot live without because they are so incredibly useful. At Matician, we are building the latter because these are the products worth spending our lives on. We want to build great products to solve real problems.

We believe that sensors and algorithms are finally good enough to reimagine home devices and apply Level 5 autonomy and mobility so that people can save time and energy bypassing repetitive and mundane tasks inside the home.

We're a small team with a singular focus on product that combines technologies such as vision, ML, structure-from-motion, and robotics. Our goal is to ship products that people love.

About the Program
Our AI Startup Residency is a one-year product-focused research position where you will develop, build and optimize machine learning, computer vision, natural language and perception algorithms for autonomous robots. You’ll play an integral role in not just in developing algorithms, but also in product development, patents and other aspects of building a company from the ground up. Unlike other residency programs that focus just on conducting research and publication, our program places heavy emphasis on the process of refining and engineering the research into a product that people can buy.

We’d love to hear from you if:

You are genuinely motivated to help those around you, including users at various levels of experience.

You are passionate about tackling large complex projects and are adaptable to learning outside your normal comfort zones.

You love diagnosing complex technical issues and providing hands-on support for hardware and software solutions.

Your curiosity to learn and grow is inversely proportional to your level of ego.

You are excited to do great work.

Qualifications
Ability to solve problems and identify areas of improvement
Ability to write clean, reliable code that can be easily maintained
Experience with Python, with experience in Tensorflow, PyTorch or Numpy a plus
Experience with working on computer vision, machine learning or NLP problems
Familiarity with modern Deep Learning algorithms
Excellent verbal and written communication skills
Comfortable with running and interpreting common statistical tests, and also with common data science/learning techniques
Ability to work in a fast-paced, autonomously driven, and demanding start-up atmosphere

Responsibilities
Collaborate with the HW, SW, and Algorithms team to bring product vision to life.
Everything involved in applying an ML model to a production use case
Designing and coding up the neural network, gathering and refining data, training and tuning the model
Deploying it at scale with high throughput and uptime
Analyzing the results in order to continuously update and improve accuracy and speed
Eligibility Requirements
Willingness to take risks
Enjoys cleaning and organizing
For international candidates without work authorization in USA, they must be graduating prior to the start of the residency for J-1 visa
Completed coursework in calculus, linear algebra, and/or their equivalent

More info | Contact: Josh Kapla | Posted on: 2020-05-18

Metric learning for instance- and category-level visual representations

We are seeking a PhD candidate to work at the Inria Center in Rennes. The PhD will be co-advised by Yannis Avrithis, Ewa Kijak and Laurent Amsaleg. The position is for three years, starting in 2020.

The goal of this PhD is to revisit the connection between classification and metric learning in visual representation learning and to extend the study of metric learning in supervision and localization settings that have mostly been studied in terms of classification. The position is part of a national research grant in collaboration with a number of academic partners. The overall goal of the project is to study visual and text representations with the purpose of one disambiguating the other and both being used for multimodal question answering over large-scale knowledge bases.

The candidate should ideally have a degree in Computer Science, Applied Mathematics or Electrical Engineering; solid mathematical background and programming skills; fluency in English language; preferably, prior experience in computer vision and deep learning, optionally as well in natural language processing.

More info | Contact: Yannis Avrithis | Posted on: 2020-05-18

Two postdoctoral researcher positions in Machine Learning and Computer Security at UC Davis NSF CHEST Center - Deadline to apply May 25

University of California Davis Center for Hardware and Embedded Systems Security and Trust (NSF CHEST) (https://nsfchest.org/) is recruiting up to two talented postdoctoral researchers to support the growth of the program and expand its research activities in the area of machine learning and computer system security. In particular, we are looking for two experts with strong scientific background, good communication skills, and solid experience in one of the following areas:

1.Machine Learning

The successful candidate will perform research in the area of applied machine learning. Some of the topics of interests are graph analytics, graph neural network, adversarial machine learning, and machine learning privacy, deep learning, reinforcement learning, and machine learning computational complexity.

2. Computer System Security

The successful candidate will perform research in the area of hardware security, computer architecture security, IoT security, and system cybersecurity.

Candidates should have completed a doctoral degree in Computer Science, Computer Engineering, or Electrical Engineering at the time of hire. Candidates with strong multidisciplinary skills covering more than one of the areas listed above are particularly encouraged to apply. Extremely well-qualified candidates with slightly different qualifications and/or research focus might be also considered under special circumstances.

Other essential qualifications include an excellent track of scientific publications; excellent English-language writing skills; ability to meet deadlines, work well with minimal direction and with a team, and produce high-quality research outputs; good time management and recordkeeping. Desirable qualifications include solid presentation skills and experience with fundraising and maintaining rapport with funding agencies.

Screening of applications will begin on May 25 and will . Interviews with applicants will be scheduled via phone or videoconference.

We offer a competitive salary and generous benefits, including health insurance, retirement plan, vacation and sick leave, and support to a successful career in scientific research. The successful candidates will be encouraged to submit the output of their work to scientific conferences and professional meetings. Pending acceptance of the work, and funding availability, they will receive support for the attendance of these meetings.

The University of California, Davis is an Equal Opportunity/Affirmative Action employer, and applications from women and under-represented minorities are encouraged.

Applicants should submit a curriculum vitae, and names/contact information of three references in a single PDF file to: hhomayoun@ucdavis.edu

Please include “Postdoc Search” in the subject line of the e-mail.

National Science Foundation CHEST Center (https://nsfchest.org/)

Center Mission

The mission of the CHEST Center is to address the research challenges that industry faces in the design, protection, and resilience of hardware from the security vulnerabilities associated with electronic hardware and embedded systems and develop the much needed workforce for government and industry.

Center Overview

The CHEST Center is funded by a combination of National Science Foundation grants and memberships by industry and non-profit institutions, and CHEST coordinates university-based research with partner needs to advance knowledge of security, assurance, and trust for electronic hardware and embedded systems.
CHEST areas of interest include identification, detection, monitoring, mitigation, and elimination of vulnerabilities that affect hardware and embedded systems. More specifically, CHEST covers all levels of hardware and embedded systems design: system, architectural, board, microprocessor, embedded system, application specific integrated circuit (ASIC), field programmable gate array (FPGA), and other circuits. Threats to hardware and embedded devices cover a broad range of attack vectors with the integration of design, manufacturing, supply chains, operations, and complex assemblies of hardware, software, and firmware. Vulnerabilities can be introduced at any hardware design level and any stage of the product lifecycle. The NSF CHEST Center addresses security, assurance, and trust across all levels and stages. The Center is inventing and disseminating technologies, practices, and guidelines to stakeholders and educating a next generation of experts. Areas of research include: hardware assurance, counterfeit detection, integrated circuit authentication, anti-reverse engineering and anti-tampering, secure communication protocols, formal verification, secure processor architectures, vulnerability analysis, infrastructure safety and resilience, and secure systems engineering.

More info | Contact: hhomayoun@ucdavis.edu | Posted on: 2020-05-18

Postdoctoral Fellow Position in NLP and/or Image Analysis

A postdoctoral fellow position is available in the Dr. Yifan Peng’s laboratory (https://pengyifan.com/) in the Department of Population Health Sciences at Weill Cornell Medicine, starting Fall 2020. Our laboratory is primarily interested in developing and applying computational approaches to biomedical text data and medical images. Our research has focused on biomedical text mining (e.g., BlueBERT, NegBio, LitVar), medical image analysis (e.g., NIH Chest X-ray, DeepSeeNet), and their combination (e.g., TieNet). The successful applicant will work on a NIH-funded project. The goal of this research project is to use radiology-specific ontology, NLP, image analysis, and DL to construct a radiology-specific knowledge graph.

Qualifications: Applicants must have training with a strong emphasis on text mining and/or image analysis. Preference will be given to individuals with expertise in big data/modeling and those with a strong interest in healthcare or life sciences. The position is open to graduating Ph.D., M.D. or M.D./Ph.D. students in Computer Science, Bioinformatics, Health informatics, or a related discipline. Current postdoctoral fellows with less than three years of postdoctoral experience are also welcomed.

Appointments are initially for two years. The positions can be extended for one or two additional years at the end of the first year based on performance. Stipends are commensurate with research experience and education.

To apply: Please submit CV and one-page research statement to Dr. Yifan Peng at pengyifan.mail@gmail.com. Shortlisted candidates will have an online interview.

More info | Contact: Yifan Peng | Posted on: 2020-05-18