Job Board

Tractable is one of the top funded AI startups in Europe, working to help accelerate the process of accident & disaster recovery and prevention. To start, we set out five years ago to build an AI visual expert for vehicle damage estimation. We are still not done, but already our AI-powered product is making a mark across three continents and solving real human-level problems.

Why bother? Put simply, by capturing the way an expert reasons over complex visual tasks, we can help produce assessments faster and to a more consistent standard. In doing so, we address the challenges of a world in which there is an increasing rate of natural disasters and accidents, getting people’s lives on track quicker and more fairly.

What’s more, our belief is that research with true impact comes from deep domain knowledge, but also that by being led by the expert and across different geographies, over time big research challenges which cross different applications and domains are surfaced. And we’ve only just begun. So if you are a researcher looking for the perfect place to be challenged daily by real research problems, but which have the potential to have a big impact on the broader world, come join us.

WHAT KIND OF PROBLEMS WILL YOU BE SOLVING?
Our AI looks at photos of damage incurred during car accidents, and is able to assess the full extent of damage to the vehicle. This involves complex visual reasoning over nested expert tasks over all parts of the car from the panels to the supporting screws, requiring both state-of-the-art computer vision and deep learning techniques and expert knowledge to solve. In the core research team, this means working on challenging research problems in areas such as: multi-image and task reasoning, domain adaptation, image segmentation and combined visual / metadata learning.

WHERE WILL YOU HAVE IMPACT?
We are always looking for someone to bring new perspectives to the team, with a strong interest in creative problem solving and taking on some of the toughest applied research challenges from a multitude of different angles, all towards the end goal of creating an AI visual expert.

Our approach is collaborative, and through working with others on the team and also using direct input from our customers, you will help to expand the reach and scope of our ML solution, working on the underlying tech that will drive step-changes in what we can offer our customers in our AI-first products.

As a Research Scientist on the core team, you will:

Work on novel solutions to some of the biggest applied research challenges in expert visual reasoning and intelligence which form the foundation of our technology
Design, implement and evaluate models combining rich visual and metadata cues to achieve this
Communicate the work of the research team both internally and externally and engage in collaborations to bring the team’s work to product

Requirements:

PhD degree in Computer Science (or related quantitative field) or MS degree in Computer Science with equivalent practical experience
Proven track-record of solving complex problems with machine learning and computer vision
Passionate about bringing impact to the world through ML / CV
Hands on experience using one of the following deep learning libraries: Tensorflow, PyTorch, Theano or similar
Preferred:

Experience applying ML to real-world problems

Here at Tractable we’re passionate about creating an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. Everyone is welcome, we don’t discriminate on the basis of any protected characteristic including race, religion or belief, gender or gender reassignment, age, sexual orientation, marital status, or disability.

We want to facilitate everyone in bringing their best selves to our interviews, so if there are any adjustments we can make for our process to be more inclusive, please let us know.

Tractable is one of the top funded AI startups in Europe, working to help accelerate the process of accident & disaster recovery and prevention. To start, we set out five years ago to build an AI visual expert for vehicle damage estimation. We are still not done, but already our AI-powered product is making a mark across three continents and solving real human-level problems.

Why bother? Put simply, by capturing the way an expert reasons over complex visual tasks, we can help produce assessments faster and to a more consistent standard. In doing so, we address the challenges of a world in which there is an increasing rate of natural disasters and accidents, getting people’s lives on track quicker and more fairly.

What’s more, our belief is that research with true impact comes from deep domain knowledge, but also that by being led by the expert and across different geographies, over time big research challenges which cross different applications and domains are surfaced. And we’ve only just begun. So if you are a researcher looking for the perfect place to be challenged daily by real research problems, but which have the potential to have a big impact on the broader world, come join us.

WHAT KIND OF PROBLEMS WILL YOU BE SOLVING?
Our AI looks at photos of damage incurred during car accidents, and is able to assess the full extent of damage to the vehicle. This involves complex visual reasoning over nested expert tasks over all parts of the car from the panels to the supporting screws, requiring both state-of-the-art computer vision and deep learning techniques and expert knowledge to solve. In the core research team, this means working on challenging research problems in areas such as: multi-image and task reasoning, domain adaptation, image segmentation and combined visual / metadata learning.

WHERE WILL YOU HAVE IMPACT?
We are always looking for someone to bring new perspectives to the team, with a strong interest in creative problem solving and taking on some of the toughest applied research challenges from a multitude of different angles, all towards the end goal of creating an AI visual expert.

As part of the core research team, you will primarily help contribute to our technical roadmap, using direct input from our customers to expand the reach and scope of our ML solution using machine learning and computer vision and working on the underlying tech that will drive step-changes in what we can offer our customers in our AI-first products.

As a Senior Applied Researcher on the core team, you will work to:

Understand and scope out ways to expand and enrich our ML solution using machine learning and computer vision
Design, implement and evaluate models combining rich visual and metadata cues to achieve this
Communicate the work of the research team both internally and externally and engage in collaborations to bring the team’s work to product

Requirements:
PhD degree in Computer Science (or related quantitative field) or MS degree in Computer Science with equivalent practical experience
2+ years experience in industry or equivalent
Proven track-record of solving complex problems with machine learning and computer vision
Want to make cutting edge research work in a real-world setting, and have a keenness to engage in all stages of the ML development process from information gathering and problem scoping to model development
Hands on experience using one of the following deep learning libraries: Tensorflow, PyTorch, Theano or similar
Experienced in mentoring and / or supervision
Preferred:
Hands-on experience driving an applied ML solution to product
Proven ability to work with a team to outline a coherent applied research agenda to solve challenging real-world problems

Here at Tractable we’re passionate about creating an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. Everyone is welcome, we don’t discriminate on the basis of any protected characteristic including race, religion or belief, gender or gender reassignment, age, sexual orientation, marital status, or disability.

We want to facilitate everyone in bringing their best selves to our interviews, so if there are any adjustments we can make for our process to be more inclusive, please let us know.

We are looking for applied machine learning engineers with a passion for developing and deploying high quality neural network solutions. We are a close knit team of highly accomplished and deeply technical machine learning engineers, who create machine learning experiences used by millions of Apple users and developers. As a member of the ML Architecture team, you will develop state-of-the-art deep learning models for problems of interest to Apple, benchmark on academic and internal datasets, and work with product teams to deploy them in Apple products.

Responsibilities

* Researching, developing and implementing innovative neural network algorithms for computer vision, NLP and related fields.
* Developing architectures which are optimized for Apple hardware.
* Developing machine learning infrastructure that can be used by product teams for developing, evaluating and deploying machine learning models.
* Transferring machine learning solutions to engineers in product teams
* Providing technical guidance to product teams on the choice of neural network architectures, data collection and evaluation.
* Providing feedback on tools and new features to machine learning platform teams.

*Key Qualifications *

* MS or PhD in Machine learning, Computer Vision, Natural Language Processing or a related field.
* 3+ years of experience developing neural network models in industry or academia.
* Proficiency in training high quality neural network models using modern machine learning frameworks like TensorFlow or PyTorch.
* Strong fundamentals in problem solving and algorithm design.
* Ability to write flawless, readable and maintainable code in Python or C++.
* Passion for creating innovative techniques and making these methods robust and generalizable.
* Strong communication skills, and ability to present deep technical ideas to audience with different skillsets.
* Collaborative team player who can work well across multiple teams.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.

We are looking for applied machine learning engineers with a passion for developing and deploying high quality neural network solutions. We are a close knit team of highly accomplished and deeply technical machine learning engineers, who create machine learning experiences used by millions of Apple users and developers. As a member of the team, you will develop state-of-the-art deep learning models for problems of interest to Apple, benchmark on academic and internal datasets, and work with product teams to deploy them in Apple products.

Responsibilities

* Researching, developing and implementing innovative neural network algorithms for computer vision, NLP and related fields.
* Developing architectures which are optimized for Apple hardware.
* Developing machine learning infrastructure that can be used by product teams for developing, evaluating and deploying machine learning models.
* Transferring machine learning solutions to engineers in product teams
* Providing technical guidance to product teams on the choice of neural network architectures, data collection and evaluation.
* Providing feedback on tools and new features to machine learning platform teams.

*Key Qualifications *

* MS or PhD in Machine learning, Computer Vision, Natural Language Processing or a related field.
* 3+ years of experience developing neural network models in industry or academia.
* Proficiency in training high quality neural network models using modern machine learning frameworks like TensorFlow or PyTorch.
* Strong fundamentals in problem solving and algorithm design.
* Ability to write flawless, readable and maintainable code in Python or C++.
* Passion for creating innovative techniques and making these methods robust and generalizable.
* Strong communication skills, and ability to present deep technical ideas to audience with different skillsets.
* Collaborative team player who can work well across multiple teams.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.

Redefine mobile photography with AI+Sensor. We are looking for extraordinary algorithm engineers to work on the image/video quality enhancement on mobile phones. You would work on core camera/ISP algorithm development and deployment. You have the chance to work with world top-tier mobile phone OEMs to define the next-generation of photo/video capture experience. The team is dynamic, fast-paced, and requires a self-motivated attitude. All levels are available.

Key qualification:
• Passionate for image quality excellence with computational photography
• Experienced with Camera ISP pipeline, image processing, and computer vision
• Experienced with Python and C/C++ programming
• Experience with programming on mobile embedded platforms, such as Qualcomm CPU/GPU/DSP/NPU (e.g., SNPE, Hexagon DSP SDK, OpenCL), with low latency, low power consumption, and real-time performance is a plus

Education:
• PhD or MS in CS, EE, or related area.

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.
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We are looking for a best-in-class remote sensing scientist with radar expertise to lead algorithm development for flood detection with high-resolution imaging radar and passive microwave sensors. 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 tasking, testing, and development of high resolution radar algorithms and passive microwave radar algorithms to map flood events. 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 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
- Lead development of an automated satellite tasking system with climate and weather data
- 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 commercial radar and passive microwave satellites
- Develop code in python, and manage databases and data assets in Google Cloud Storage, Google Earth Engine Assets, and GitHub
- 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 radar remote sensing
- Code proficiency (preferably 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
- Prioritizes 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 for data fusion
- Experience with InSAR/Interferometry and passive microwave sensors
- Experience working with climate, weather forecasting, or other to predict extreme events
- Understanding of hydrology and physically-based flood models
- Contributing to a shared codebase on GitHub with multiple collaborators
- 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: Senior Remote Sensing Scientist, Cloud to Street
- Attached CV/resume
- Paragraph expressing interest
- Relevant publications or past projects

Applications will be accepted until the position is filled.

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.

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 remote sensing scientist to join our research and development team. You should apply if you are eager to employ your top notch geospatial talents and coding skills toward designing new tools to reduce the impact of catastrophic flooding in low and middle-income countries. You will help unlock satellite data to build new types of financial protection and insurance. 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. If you are committed to building an innovative and sustainable organization designed to reduce scientific barriers to flood information, this job is for you!

Primary Responsibilities
- Incorporate new flood detection methods at the forefront of science/technology for improving flood data extraction from satellite imagery
- Work with a team of scientists to translate scientific advances from remote sensing, computer vision, and machine learning into useful products by end-users
- Identify scientific advances in the literature and translate ideas into figures, code, and real world impact with our deployment team working with end-users
- Work with the Chief Science Officer and R&D lab to conceive, design and test proof of concepts for humanitarian and insurance applications
- 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
- MS or BS with 3 years of industry experience in geography, earth science, atmospheric science, engineering, computer science, or a related field with a focus on remote sensing and/or geospatial analysis
- Coding proficiency with geospatial Python packages (e.g. GDAL, rasterio, shapely), Google Earth Engine JavaScript/Python APIs.
- Experience working with a variety of satellite data types (optical, SAR, high-resolution)
- Self-starter with ability to work within a fast-paced and rapid-evolving startup
- Proven ability to wrangle data and condense it into meaningful insights through figures
- Prioritizes justice, diversity, science, and solidarity with vulnerable communities

Useful Experience
- Understanding of climatology, hydrology, machine learning, or crowdsourced data science methods and techniques
- Experience contributing to a shared codebase on GitHub with multiple collaborators
- Experience using virtual machines on Google Cloud or similar platform
- Experience working with geospatial databases (e.g. PostgreSQL)
- Experience 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: Remote Sensing Scientist, Cloud to Street
- Attached CV/resume
- Paragraph expressing interest
- Example of past work deriving insights from large geospatial datasets (e.g. through a publication, data science or class project, ipython notebook, google co-lab, or github with code+graphs, etc.)

Applications will be accepted until the position is filled, with the intent of starting July 15 2020.

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.

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.

Overview
The position is funded under an Australian National Health and Medical research Council Grant: “Automated methods for evaluating structural vascular disease”. Working with the principal awardees, A/Prof. Joshua Lewis, and Prof. David Suter, the successful applicant will contribute to novel theory and methods in applying Deep Learning methods to problems in Medical and Health related image analysis. Particularly, the key focus will be to develop and assess methods to extract calcification measures off images of the abdominal aorta and correlate these measures with clinical data.

The Role
The School is looking for enthusiastic Post-doctoral Research Fellow who possesses knowledge and expertise in areas including:
• Machine Learning
• Deep Learning
• Computer Vision
• Mathematics and Statistics

What you will do
The successful candidate/s are expected to promote and publish in these areas of research and engage in the supervision and training of research students and project team members.

Skills & Experience
You must have a PhD in an appropriate field (e.g., Computer Science, Mathematics, Electrical Engineering) and expertise in one or more of the areas listed above will be an advantage. Strong mathematical ability will be highly regarded.

The successful applicant will also demonstrate personal attributes that are congruent with the University’s values of Integrity, Respect, Rational Inquiry and Personal Excellence.

Benefits & Remuneration
This full-time, fixed-term position attracts remuneration of $89,524 to $118,912 pa ALEVA-B plus 9.5% University superannuation contribution for contracts up to 2 years, and 17% University superannuation contribution for contracts over 2 years.
How to Apply
Application is through the University recruitment website and you should include pdf copies of a full CV (including publication list – please reference impact factors and citations), relevant documents such transcripts of undergraduate results, and a covering letter briefly summarising your suitability for the role and including the names and contact details of at least three relevant referees.

Closing Date
Applications close on Tuesday 16 June 2020 at 11:30pm AWST

Overview
The position is funded under an Australian Research Council Discovery Grant: “Tensor and Hypergraph Methods in Fitting Visual Data”. Working with the awardee, Prof. David Suter, the successful applicant will contribute to novel theory and methods in apply Tensor/Hypergraph methods to computer vision problems. The scope particularly includes (but is not restricted to) “clustering” based methods where the affinity tensor/hypergraph plays a key role.

The Role
The School is looking for enthusiastic Post-doctoral Research Fellow who possesses knowledge and expertise in areas including:
• Machine Learning
• Data mining
• Computer Vision
• Mathematics and Statistics

What you will do
The successful candidate/s are expected to promote and publish in these areas of research and engage in the supervision and training of research students and project team members.

Skills & Experience
You must have a PhD in an appropriate field (e.g., Computer Science, Mathematics, Electrical Engineering) and expertise in one or more of the areas listed above will be an advantage. Strong mathematical ability will be highly regarded.

The successful applicant will also demonstrate personal attributes that are congruent with the University’s values of Integrity, Respect, Rational Inquiry and Personal Excellence.

Benefits & Remuneration
This full-time, fixed-term position attracts remuneration of $89,524 to $95,855 plus 9.5% University superannuation contribution for contracts up to 2 years, and 17% University superannuation contribution for contracts over 2 years.
How to Apply
Application is through the University recruitment website and you should include PDF copies of a full CV (including publication list – please reference impact factors and citations), relevant documents such transcripts of undergraduate results, and a covering letter briefly summarising your suitability for the role and including the names and contact details of at least three relevant referees.

Closing Date
Applications close on Tuesday 16 June 2020 at 11:30pm AWST

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.

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.

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.

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.

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

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.

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

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

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.

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/

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/

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/

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.

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.

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.