Physics/AI Jobs

As a hub for the intersection of Physics and AI in the Boston area and beyond, we are happy to share job opportunities at this intersection as we become aware of them.

To include a job post on this page, email, including the job title, job description, and application deadline.

Note: These are jobs external to IAIFI. For IAIFI-related job opportunities, see our IAIFI Jobs page.

Academic Opportunities

Faculty Opportunities

Tenured or Tenure-Track Faculty Position in Astronomy and Astrophysics
Penn State University Park
Deadline: 2023-02-24 | Apply

Details The Department of Astronomy and Astrophysics at The Pennsylvania State University, University Park campus, invites applications for a tenured/tenure-track faculty position. We are seeking outstanding candidates with promise to establish a vibrant research program within our department, especially in the area of Astronomical Instrumentation. We will consider appointments at the rank of assistant professor as well as appointments at higher ranks, depending on the qualifications of the applicant.

Assistant/Associate Professor in Statistics
ENSAI, France
Deadline: 2023-03-31 | Apply

Details ENSAI, the French graduate-level engineering school specialized in Statistics, Data Science and Economics, is currently inviting applications for a position as Associate or Assistant Professor in Statistics. The appointment starts in September, 2023, at the earliest. At the level of Assistant Professor, the position is for an initial three-year term renewable for another three years before the tenure evaluation. At the level of Associate Professor, the position is tenured. Salary is competitive according to qualifications. The teaching duties are reduced compared to French university standards. At the appointment, knowledge of French is not required but it is expected that the appointee will acquire a workable knowledge of French in a reasonable time. The school offers resources to learn French. PhD in Statistics or related fields required. All the areas of statistics are welcome. Applicants will have demonstrated strong ability to teach Master level courses in Applied Mathematics and Statistics for the engineers and to supervise projects in Applied Statistics. At the Associate Professor level, the candidate will have an outstanding research record and is expected to supervise PhD students.

Assistant/Associate Professor in Computer Science
ENSAI, France
Deadline: 2023-03-31 | Apply

Details ENSAI, the French graduate-level engineering school specialized in Statistics, Data Science and Economics, is currently inviting applications for a position as Associate Professor in Computer Science and Machine Learning. The appointment starts in September, 2023, at the earliest. PhD or HDR in Computer Science, with an expertise in Statistics or Machine Learning required. ENSAI is involved in the EUR Digisport and the EUR CyberSchool, so knowledge on related fields would be a plus. The applicant will have demonstrated strong ability to teach courses in Computer Science, related in particular to Statistics, and to supervise projects. At the Associate Professor level, the candidate will have an outstanding research record and is expected to supervise PhD students.

Postdoc Opportunities

Postdoctoral Research Associate, Xtreme Astrophysics Group
Georgia Institute of Technology
Deadline: 2023-02-18 | Apply

Details The Xtreme Astrophysics group at the Georgia Institute of Technology invites applications for two Postdoctoral Research Associate positions in the fields of computational plasma physics and/or machine learning. The successful applicants will join a group led by Profs. Feryal Ozel and Dimitrios Psaltis, with research interests in high-performance computing simulations of plasmas and radiation from microphysical to macroscopic scales. The initial appointment will be for 2 years, with a possible extension for two additional years, depending on performance and funding.

Postdoctoral Researcher in Statistics and Machine Learning
University of Chicago

Details Applications are invited for a postdoctoral researcher working under the supervision of Prof. Bryon Aragam. The candidate will be given the opportunity to pursue a broad research agenda at the intersection of statistics and machine learning and will ideally have a background in at least one of the following areas: latent variable models, deep generative models, causal inference, nonparametric statistics, learning theory, or graphical models.

Postdoctoral Fellowship, Generative Modeling in Machine Learning
UMEÅ University
Deadline: 2023-02-12 | Apply

Details The Department of Computing Science is characterized by world-leading research in many different areas, and is ranked highly in international comparison. The department has been growing rapidly in recent years, with a focus on creating an inclusive and bottom-up driven research environment. To further strengthen our numbers, we are now offering a postdoctoral scholarship to develop generative machine learning models within the project “AI in Medical Imaging”. Our workplace consists of a diverse set of people from different nationalities, background and fields.

Postdoc, ML applied to space weather forecast
Center for mathematical Plasma-Astrophysics (CmPA), KULeuven
Deadline: 2023-03-31 | Apply

Details The Centre for mathematical Plasma-Astrophysics (CmPA) of the KULeuven is looking for a postdoc to study and develop modern AI/ML techniques to detect and forecast dangerous activity in space weather, considering ionosphere, magnetosphere and solar active regions. Within the new four-year Belgian DEFRA project AIDefSpace, we are processing different data sources relative to the ionosphere and the magnetosphere and high-resolution magnetograms and multi-spectral images of the Sun. Using advanced machine learning techniques, we want to make nowcasts and forecasts of space weather and discover signatures of flaring activity and other potentially dangerous conditions. The tools developed will be compared to existing models and proposed as new services for the Belgian and European space weather centres. We look for a candidate with a PhD in Space Science, Physics, Engineering or in AI/ML with a background in computer sciences applied to physics. The ideal candidate has experience or is interested in learning the bases on machine learning, including neural networks, data processing and unsupervised learning. It is desirable that the candidate has already some knowledge on Python programming and of the domain of physics related to space sciences: e.g. particle physics, plasma physics, aerospace engineering, fluid dynamics.

Industry Opportunities

Technology Venture Fellow in ML and AI
The Engine

Details The Engine is looking for outstanding scientists, engineers and budding entrepreneurs to work together with our investment team in the rapidly developing field of Artificial Intelligence / Machine Learning (AI/ML). The Technology Venture Fellowship is a part-time role that will allow applicants to dive deep into AI/ML systems that are achieving unprecedented levels of performance. You will be able to apply your training and scientific expertise and combine it with business-oriented thinking in the context of venture investments. The Technology Venture Fellowship program will give you an experience rooted deeply in science and engineering while allowing you to learn about early-stage company formation and venture investments in Tough Tech.

AI Researcher
Autodesk AI Lab

Details As an AI Research Scientist at Autodesk Research, you will be doing fundamental and applied research that will help our customers imagine, design, and make a better world. We are a team of scientists, researchers, engineers, and designers working together on projects that range from learning-based design systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, architectural design and construction. As a member of the AI Lab in Autodesk Research you are an experts in research areas such as artificial intelligence, deep learning, machine learning, computer vision, reinforcement learning, information retrieval, natural language processing, and knowledge representation & reasoning.

Senior Research Software Development Engineer (Deep Learning for Material Generation)

Details Over the coming decade, deep learning looks set to have a transformational impact on the natural sciences. The consequences are potentially far-reaching and could dramatically improve our ability to model and predict natural phenomena over widely varying scales of space and time. Our AI4Science team encompasses world experts in machine learning, computational chemistry, material science, quantum physics, molecular biology, fluid dynamics, software engineering, and other disciplines, who are working together to tackle some of the most pressing challenges in this field. For our lab in Cambridge, we are seeking Research Software Development Engineer (RSDE) candidates in the area of deep learning for material generation. The successful applicant is expected to contribute to cutting-edge technological developments of generative models, reinforcement learning, and graph neural networks for materials generation, which has the potential to discover breakthrough materials for a broad range of applications.

Postdoctoral Fellow in AI research
Vector Institute
Deadline: 2023-02-28 | Apply

Details The Vector Institute invites applications for Postdoctoral Fellows who are working on cutting-edge fundamental research in machine learning and deep learning algorithms and their applications. Areas of research include: computer vision; generative models; healthcare (computational biology, genomics); natural language processing; optimization; reinforcement learning; statistical learning theory; sequential decision making; security, privacy, and fairness; and quantum computing. The standard term for a Postdoctoral Fellow position is 1–2 years, with a possible extension to 3 years. Also available is the opportunity for eligible individuals to complete a placement at Vector before going on to take a faculty role elsewhere.