Job Board

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.

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

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

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

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.

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

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

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.

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.

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.

The Centre for Vision Speech and Signal Processing (CVSSP) at the University of Surrey seeks to recruit an outstanding postdoctoral researcher in the fields of Computer Vision and Deep Learning. The post is part for 2.5 years as part of EPSRC funded research project.

The project is focussed on developing a new deep-learning toolkit and techniques, to support state-of-the-art deep-learning with modern asynchronous visual sensors (such as event cameras by prophesee.ai or inivation.com). Unlike initial research in this area, we will attempt to avoid intermediary image representations, instead developing techniques that operate on the raw event stream. This will allow the special properties of the sensor (particularly it's low latency) to be preserved. Applications of this research will range from robotics to autonomous vehicles and more.

Successful applicants will work under the supervision of Dr Simon Hadfield, with full access to the resources provided by Surrey’s Centre for Vision Speech and Signal Processing. CVSSP is the largest UK academic research institute focussed on computer vision & machine learning (around 200 active research staff). This role provides the opportunity to work alongside world leading researchers in computer vision and deep learning, while also being able to interact remotely with a wealth of industrial collaborators.

By the start date of the post, the potential applicant should either hold, or have submitted, a PhD in a field closely related Computer Vision and Machine Learning. A strong background in deep-learning is a must, as are strong programming skills. Prior experience with asynchronous visual sensors, or the Robot Operating System are not required, but are advantageous. Furthermore, the potential applicant should be able to drive their own research direction within the scope of the project, and have an interest in PhD co-supervision opportunities on aligned topics.

One to two openings are now available for a research appointment in the Department of Medical Physics at the postdoctoral level for individuals interested in medical image analysis research. The two-year research projects will focus on the development of advance deep learning-based analysis of multi-parametric MRI images for automated detection and volumetric segmentation of dominant prostatic lesions for aiding in real-time MR guided radiation therapy on the new MRI guided linear accelerator (MR-LINAC) systems. The project entails development of deep learning algorithms for detecting and classifying domain index lesion, volumetric segmentation, and tracking of whole prostate gland and the dominant lesion for real time guidance. This project involves working with multi-disciplinary scientists including computer scientists, MRI physicists, radiation oncologists, and radiologists.

Successful execution on the project is expected to result in high impact publications, as well as implementation of the software prototypes in to the clinical treatment planning workflow in coordination with our team of developers and physicists. Ideal candidates must have strong programming background (python) with knowledge of machine learning applied to computer vision or medical image analysis. Deep learning knowledge and some image registration/segmentation development experience is highly desirable. Candidates are expected to have excellent written and oral communication skills for writing manuscripts and presenting to multi-disciplinary audiences.

The Department of Medical Physics consists of over forty faculty physicists plus support staff working on various physical problems related to the diagnosis and treatment of cancer.

Memorial Sloan Kettering Cancer Center is located on the Upper East Side of Manhattan, and is recognized as a world leader in clinical cancer care and research.

Interested candidates should send a resume and list of three references by May 31, 2020 via e-mail, including the project title in the application, to:

Christopher Watchman, Ph.D.
Education Director and Associate Attending Physicist
Department of Medical Physics
Memorial Sloan Kettering Cancer Center
1275 York Ave.
New York, NY 10065
e-mail: watchmac@mskcc.org

Are you inspired by building new technologies to benefit customers? Do you dream of being at the forefront of robotics and autonomous system technology? Would you enjoy working in a fast paced, highly collaborative, start-up like environment? If you answered yes to any of these then you've got to check out the Amazon Scout team.

We’ve been hard at work developing a new, fully-electric delivery system – Amazon Scout – designed to get packages to customers using autonomous delivery devices. These devices were created by Amazon, are the size of a small cooler, and roll along sidewalks at a walking pace. We developed Amazon Scout at our research and development lab in Seattle, ensuring the devices can safely and efficiently navigate around pets, pedestrians and anything else in their path.

The Amazon Scout team shares a passion for innovation using advanced technologies, a love of solving complex challenges, and a desire to impact customers in a meaningful way. We're looking for individuals who like dealing with ambiguity, solving hard, large scale problems, and working in a startup like environment. To learn more about Amazon Scout, check out our Amazon Day One Blog post here: http://amazon.com/scout

As a Software Development Engineer specializing in Computer Vision and Perception, you have the chance to help develop cutting-edge robotic technology by combining perception, computer vision, and deep learning.

In this job you will:
· Collaborate with top-notch research scientists, software development engineers and hardware engineers to build high-quality production code
· Develop the core software including defining, scoping and launching a highly impactful new service
· Investigate, prototype and deliver innovative system solutions in a start-up like environment
· Work in an Agile/Scrum environment to deliver high quality software

You are a person with a commitment to team work, who enjoys working on complex systems, is customer centric, and thrives on the challenge of prototyping new systems that will eventually operate at Amazon scale.

BASIC QUALIFICATIONS
· Bachelor’s degree (or higher) in Computer Science or a related discipline
· 3+ years of software development experience developing computer vision, perception, and/or deep learning solutions for robots, autonomous cars or similar
· 3+ years of experience developing software with C++ or Python

PREFERRED QUALIFICATIONS
· Strong computer science fundamentals in design, algorithms, and data structures.
· Master’s degree or higher in Computer Science or related field
· Experience building mission critical, highly available systems and operating 24x7 services
· Experience building safety-critical software

Amazon is an Equal Opportunity-Affirmative Action Employer - Female/Minority/Disability/Veteran/Gender Identity/Sexual Orientation/Age.

Are you inspired by building new technologies to benefit customers? Do you dream of being at the forefront of robotics and autonomous system technology? Would you enjoy working in a fast paced, highly collaborative, start-up like environment? If you answered yes to any of these then you've got to check out the Amazon Scout team.

We’ve been hard at work developing a new, fully-electric delivery system – Amazon Scout – designed to get packages to customers using autonomous delivery devices. These devices were created by Amazon, are the size of a small cooler, and roll along sidewalks at a walking pace. We developed Amazon Scout at our research and development lab in Seattle, ensuring the devices can safely and efficiently navigate around pets, pedestrians and anything else in their path.

The Amazon Scout team shares a passion for innovation using advanced technologies, a love of solving complex challenges, and a desire to impact customers in a meaningful way. We're looking for individuals who like dealing with ambiguity, solving hard, large scale problems, and working in a startup like environment. To learn more about Amazon Scout, check out our Amazon Day One Blog post here: http://amazon.com/scout
As an Applied Scientist specializing in Computer Vision, you will combine cutting-edge Deep Learning techniques with classical Computer Vision to create intelligent systems.

In this job you will:

· Collaborate closely with Robotics scientists and Hardware teams to develop perception systems for Robots.
· Take responsibility for technical problem solving, including creatively meeting product objectives and developing best practices.
· Interact with teammates in variety of roles to accomplish your goals.
· Identify and initiate investigations of new technologies, prototype and test solutions for product features, and design and validate designs that deliver an exceptional user experience.
· Recruit, hire and develop other Applied Scientists.

You are a person with a commitment to team work, who enjoys working on complex systems, is customer centric, and thrives on the challenge of prototyping new systems that will eventually operate at world-wide scale.

BASIC QUALIFICATIONS
· Ph.D in CS Computer Vision, Machine Learning, Statistics, or in a highly quantitative field
· A thorough understanding of both best practices for practical systems and the state-of-the-art in academic research
· Experience developing software in C++ or Python.

PREFERRED QUALIFICATIONS
· 3+ years of industry experience in robotics
· 3+ years of relevant research experience in computer vision and machine learning.
· Experience as a technical lead on a small team.
· Experience with production computer vision and machine learning systems

Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age

The Wallenberg AI, Autonomous Systems and Software Program (WASP) is
Sweden’s largest individual research program ever; a major national
initiative for strategically motivated basic research, education and
faculty recruitment (see https://wasp-sweden.org). WASP comprises five
Swedish full partner universities and a substantial part of Swedish
industry and commerce. The WASP initiative includes among many
instruments an international recruitment program and the present
announcement aims to strengthen Linköping University specifically in
the field of machine learning within the AI focus-area of WASP. The
goal is to complement the existing excellence in, among others, the
area of Computer Vision (Michael Felsberg).

For this purpose, we seek competence in Machine Learning with focus
particularly on methods, algorithms, and mathematical analysis relevant
to Computer Vision. The developed methods and mathematical tools will
aim at a better understanding of the theories and processes within
statistical and deep learning-based systems.

Possible research topics should match one or more of WASP focus
areas 1) Representation learning and grounding, 2) Sequential decision-
making and reinforcement learning, 3) Learning from small data sets,
GANs and incremental learning, and 4) Multi-task and transfer learning.
Examples for such topics are, but are not limited to, handling of
uncertain input data, propagation of confidences, detection of
anomalies, few-shot and model-agnostic learning, robustness to polluted
training data, enforcement of hard constraints, explainability of
complex networks, and explorative data acquisition. The research fellow
will also explore application areas of this research, e.g., within
forestry, agriculture technology, and synthetic environments for
training autonomous driving.

A successful candidate addressing the area above will be affiliated
with the Computer Vision Laboratory (CVL) at the Department of
Electrical Engineering. Unlike other international universities, thanks
to the teachers' exemption (Lärarundantaget - i.e. the exemption from
employers’ rights to their employees’ patentable inventions),
researchers/academic staff at Swedish universities and colleges of
higher education are given the rights to their own research results.
LiU has support for researchers as inventors, with a unit at the
University that helps the teacher to patent ideas, even fund the
patent application, while the patent is still owned by the researcher.
LiU offers an excellent research environment for you, while you may
choose living in urban or rural environments with commuting distance of
15 min.

Apply before June 23!

I am looking for a highly motivated postdoc to join my research group at Chalmers. It is a fixed term position (two years) with lots of freedom to pursue basic research in computer vision and machine learning!

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. We are excited that the system has helped the police solve thousands of crimes that were unsolved in the past, making our society safer.

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. We are excited that the system has helped the police solve thousands of crimes that were unsolved in the past, making our society safer.

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.

Position description: The research project will focus on developing machine learning/deep learning methods for fundamental computer vision problems including object motion tracking, segmentation, 3D reconstruction, classification and image captioning in 2D/3D images including RGBD images, remote sensing data, 3D CT/MRI medical images and biomedical text. The successful applicant will contribute to research and development of efficient and low cost machine learning/deep learning tools with potential application on autonomous driving cars, large scale 3D scene reconstruction, mapping and localization, video surveillance, human computer interaction, virtual reality, augmented reality, computer-assisted surgery and computer aided disease diagnosis. The group’s works appeared in top journals and conferences including CVPR, ECCV, MICCAI, TPAMI. For a complete list of her works and more information about her research, please visit: https://www.yingyingzhu.net
Qualifications: Successful applicants will have a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, Physics and other related fields, and strong motivation to do cutting edge research in computer vision and machine learning. Additionally, strong quantitative skills and a strong programming background (Python,C++) are desired. Previous research experiences in related fields and scientific publications in journals/conferences are appreciated but not required.

About the department:
UT Arlington Computer Science has top research ranking based on the past ten-year publications at:
Artificial Intelligence (ranks #30 in USA)
Computer Vision (ranks #34 in USA)
Machine Learning & Data Mining (ranks #59 in USA)
Computer Engineering #80, Computer Science #91 [U.S. News & World Report 2019]

Strong enrollment growth in CSE: Currently 1,363 Bachelor’s, 747 Master's, 132 Ph.D.

R1 university [Carnegie Classification of Institutions of Higher Education]

The application materials will be reviewed immediately once received. The expected starting time is Fall 2020 or Spring 2021. Interested candidates should send a cover letter describing your research interests, CV (including undergraduate GPA and ranking, transcripts if applicable), and contact information of three references to Dr. Yingying Zhu: zhuyingying2@gmail.com.
Check here for detailed admission requirements (e.g., GRE and TOEFL scores)
https://catalog.uta.edu/academicregulations/admissions/graduate/

Position description: The research project will focus on developing machine learning/deep learning methods for fundamental computer vision problems including object motion tracking, segmentation, 3D reconstruction, classification and image captioning in 2D/3D images including RGBD images, remote sensing data, 3D CT/MRI medical images and biomedical text. The successful applicant will contribute to research and development of efficient and low cost machine learning/deep learning tools with potential application on autonomous driving cars, large scale 3D scene reconstruction, mapping and localization, video surveillance, human computer interaction, virtual reality, augmented reality, computer-assisted surgery and computer aided disease diagnosis. The group’s works appeared in top journals and conferences including CVPR, ECCV, MICCAI, TPAMI. For a complete list of her works and more information about her research, please visit: https://www.yingyingzhu.net
Qualifications: Successful applicants will have a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, Physics and other related fields, and strong motivation to do cutting edge research in computer vision and machine learning. Additionally, strong quantitative skills and a strong programming background (Python,C++) are desired. Previous research experiences in related fields and scientific publications in journals/conferences are appreciated but not required.

About the department:
UT Arlington Computer Science has top research ranking based on the past ten-year publications at:
Artificial Intelligence (ranks #30 in USA)
Computer Vision (ranks #34 in USA)
Machine Learning & Data Mining (ranks #59 in USA)
Computer Engineering #80, Computer Science #91 [U.S. News & World Report 2019]

Strong enrollment growth in CSE: Currently 1,363 Bachelor’s, 747 Master's, 132 Ph.D.

R1 university [Carnegie Classification of Institutions of Higher Education]

The application materials will be reviewed immediately once received. The expected starting time is Fall 2020 or Spring 2021. Interested candidates should send a cover letter describing your research interests, CV (including undergraduate GPA and ranking, transcripts if applicable), and contact information of three references to Dr. Yingying Zhu: zhuyingying2@gmail.com.
Check here for detailed admission requirements (e.g., GRE and TOEFL scores)
https://catalog.uta.edu/academicregulations/admissions/graduate/

The Institute of High-Performance Computing (IHPC) of the Agency for Science, Technology and Research (A*STAR) Singapore has a Research Engineer opening in the areas of Human Action Anticipation and Action Forecasting. This position is for 24-months with potential extension. The candidate should be able to develop Computer Vision and Machine learning algorithms for human action recognition and action anticipation. This position is research focused and the candidate must have a bachelor or master’s degree in computer science, Electrical & Electronics Engineering, or related disciplines. Fluency in Python and Pytorch or Tensoflow is required. Knowledge of Machine Learning, Deep Learning, Deep Generative models, Motion estimation, and Computer Vision is essential. Candidates who are looking forward to starting PhD are given great exposure and training, with possibly having many scholarship opportunities provided by A*STAR Singapore. Candidates who are Singaporeans and residents are given priority, but we also accept international candidates. The project is funded by AI Singapore and focuses on both theory and applications.

Candidates with prior publications in CVPR, ECCV, ICCV, ICLR, AAAI, BMVC, ACCV, TPAMI, IJCV and TIP etc. are preferred. You will join a diverse team consisting of many scientists and Engineers having expertise in Computer Vision, Machine Learning and NLP. You will be primarily working with Dr. Basura Fernando (https://basurafernando.github.io/ ). If interested, please send your CV.

The Company

We are a fast-paced startup building the next generation surgical robot platform. We’re a diverse team dedicated to creating non-invasive solutions that provide clinical value for both patients and doctors. Working here means joining an experienced startup team that is excited and passionate about creating world class products. Founded by a serial entrepreneur with 2 successful exits, the team includes former engineers from top medical robotics companies. We are a well-funded startup and expect talented, motivated, ambitious and interesting co-workers.

Role and Responsibilities

* Work with marketing and users to define and iterate requirements
* Research, prototype, iterate algorithmic solutions to computer vision problems for surgical planning and navigation
* Contribute high quality code to create a medical product that is safe and effective
* Support testing and documentation

Job / Skill Requirements

* MS/PhD degree in Computer Science, Electrical Engineering or other related programs
* Solid foundation on mathematics and analytical skills
* Solid training and hands-on experience in geometric computer vision including camera calibration, stereo reconstruction, pose estimation, structure from motion, SLAM
* Working knowledge and hands-on experience with Machine learning and Deep learning
* Strong development skills using C++, C# and/or Python (and the desire to learn new techniques and tools)
* Object Oriented Programming understanding and experience
* Experience with volumetric medical image segmentation, registration or reconstruction is preferred
* Experience or knowledge with estimation, navigation and sensor fusion is a plus
* Familiarity with tools such as OpenCV, ITK, DL frameworks
Industry experience is preferred but not required

As an intern of a computer vision team at Apple, you will use your deep understanding of computer vision, machine learning, and artificial intelligence to tackle meaningful technical problems, collaborate with the most innovative product development teams in the world, and transfer your ideas into solutions in the next generation of Apple products. You will perform fundamental research by defining, designing, implementing and evaluating algorithms involving unrivaled data and objectives.

https://bit.ly/apple-cvpr2020-intern

As a member of a computer vision team at Apple, you will use your deep understanding of computer vision, machine learning, and artificial intelligence to tackle meaningful technical problems, collaborate with the most innovative product development teams in the world, and transfer your ideas into solutions in the next generation of Apple products. You will perform fundamental research by defining, designing, implementing and evaluating algorithms involving unrivaled data and objectives. You will also actively engage with the academic community by collaborating with universities, publishing and presenting your work, and attending conferences.

https://bit.ly/apple-cvpr2020

AQUACORP is a Spanish Deep Tech startup looking for a post-doc researcher to lead a small team focused on developing Deep Learning and Computer Vision-based solutions to analyse water quality. The post-doc will work closely with experienced academic researchers from the University of Leon, which will provide the opportunity of publishing papers in relevant journals and conferences.

We are looking for candidates with a strong academic record and a PhD degree in computer science with expertise in machine learning and computer vision. Good programming skills in Python and experience with deep learning frameworks as well as publications in top conferences or journals are a must. The candidate has to be highly motivated, task-oriented and very good teamwork skills are required.

AQUACORP mission is leading the surface water quality remote monitorization, through water images and computer vision. Our main goal is “to help water pollution managers by bringing to the market one scalable, affordable and cost-effective technology to monitor every single effluent, make an adequate water quality management and take care of watery ecosystems´ sustainability”.

AQUACORP is formed by a team of entrepreneurial talent comprised of software and hardware developers and scientific and biology watery ecosystems & wastewater treatment specialist. Our ambition is to become a leading technology enabler on the water quality analysis space by developing an innovative Deep Tech platform, a Water-quality Early Alert System (WEAS), and to disrupt the surface water quality remote analysis and the environment monitoring industry.

OUR GAME-CHANGING SOLUTION: A Water-quality Early Alert System(WEAS) based on water image analysis to remotely and real-time evaluate water pollution levels.

We offer:
* Work in a global challenge, a 10 years project.
* Work from home / remotely whenever you need to, or want to.
* Competitive salary and equity.
* Fun, energetic work environment, and daily perks - snacks, drinks, catered lunch twice a week
* Opportunity to work with a product-focused on making the world sustainable
* Opportunity for creativity, entrepreneurship and ultimate career happiness.
* Collaborating with people passionate about work, cultivating dedication, motivation, and discipline.
* Strong interpersonal skills and work ethic.
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And much more!