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.
IAIFI Jobs
The following positions are at IAIFI-affiliated universities and therefore have the potential for IAIFI involvement; they are not necessarily directly hired by IAIFI.
Faculty Opportunities
Tenure-track Professor in Computer Science and Kempner Institute Investigator
Harvard John A. Paulson School of Engineering and Applied Sciences
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Details
The Computer Science area of the John A. Paulson School of Engineering and Applied Sciences (SEAS) and the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University are seeking applicants for a tenure-track position specializing in Machine Learning and Artificial Intelligence, with an expected start date of July 1, 2025.We are particularly interested in candidates with strong foundations in deep learning, generative AI, foundational models, and LLMs, with interest to apply these technologies to one or more domains including computational biology and the sciences, NLP, and computer vision. The successful candidate will be expected to lead an innovative research program that advances our understanding of and increases innovation in AI and ML, encompassing the development of new methodologies and models.
Postdoc Opportunities
Postdoctoral researchers at any of the partner institutions may collaborate with IAIFI researchers to become a Junior Investigator.
Graduate Student Opportunities
IAIFI does not have a dedicated PhD program, but PhD students at any of the partner institutions may collaborate with IAIFI researchers to become a Junior Investigator.
Other Opportunities
Post-Baccalaureate Program at Kempner Institute for the Study of Natural and Artificial Intelligence
Harvard University, Cambridge, Massachusetts
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Details
Applications are open for the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University's Post-Baccalaureate Program.Offered in partnership with the Harvard Griffin Graduate School of Arts and Sciences (GSAS) Office for Equity, Diversity, Inclusion and Belonging, the Kempner post-baccalaureate program is a fully funded two-year training program designed to prepare recent college graduates for PhD programs in intelligence research, including fields like computer science, machine learning, neurobiology, and cognitive science.
Research Scientist 1
Kavli Institute for Astrophysics and Space Research at MIT, Cambridge, Massachusetts
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Details
RESEARCH SCIENTIST 1, Kavli Institute for Astrophysics and Space Research, to cover research for Cosmic Explorer, the concept for a next-generation gravitational-wave detector, particularly the development of computational approaches to study critical aspects of the Cosmic Explorer design, like stray-light mitigation; aid the Cosmic Explorer Project Scientist and Project Engineer in the integration of these and other studies of CE design aspects into the overall observatory design; develop computational approaches (numerical/analytical models) to advance the Cosmic Explorer design, with a focus on stray-light modeling and mitigation techniques in Cosmic Explorer; document the findings to support the conceptual design of Cosmic Explorer, and work with the Project Scientist and Project Engineer in the integration of these and other findings into the overall Cosmic Explorer observatory design; interact with a large group of scientists and engineers working on the Cosmic Explorer design across several institutions and may require the preparation of research narratives for grant proposals and occasional short stay visits to the other institutions working on stray-light mitigation for Cosmic Explorer, including Bard College and Caltech.Feel free to contact Lisa Barsotti with any questions: lisabar@mit.edu
Academic Opportunities
Faculty Opportunities
Associate Professor/Professor in Machine Learning
UiT (The Arctic University of Norway), Tromsø, Norway
Deadline: 2025-01-27 | Apply
Details
The Department of Physics and Technology has up to three open permanent positions as Associate Professor and/or Professor. Early career scientists, with a promising CV, as well as experienced candidates are invited to apply, respectively for Associate and full Professor.The faculty members will join the UiT Machine Learning Group. The group is internationally recognized, with research ranging from foundational machine learning methodology and algorithms to applied AI development. The range of applications is wide, with a particular focus on healthcare. The new faculty members shall further strengthen the scientific excellence and high-profile of the group, notably in the Centre of Research-based Innovation SFI Visual Intelligence, which is headed by the group, and the Centre of Excellence SFF Integreat – The Norwegian Centre for Knowledge-based Machine Learning.
The workplace is at UiT in Tromsø. You must be able to start in the position in Tromsø within 6 months after receiving the offer.
Assistant Professor of Computer Science, Applied Machine Learning/AI
Dartmouth College, Hanover, New Hampshire
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Details
The Department of Computer Science invites applications for a full-time tenure-track position at the rank of Assistant Professor in the broad area of Applied Machine Learning/AI. Core technical contributions could come from multiple areas, including but not limited to: computational health, visual computing, music technology, cybersecurity, neuroscience, Human-Computer Interaction (HCI), Computational Linguistics, and digital arts. Applicants should have a track record of publications in CS/machine learning-related fields.Assistant Teaching Professor, Data Science and Analytics Program
Georgetown University, Washington, D.C.
Deadline: 2025-01-08 | Apply
Details
The Georgetown University Graduate Data Science and Analytics Program invites applicants for a full-time, non-tenure line position as an Assistant Teaching Professor.The successful candidate will teach three graduate-level courses per semester (Fall and Spring) and will participate in administrative tasks, such as admissions and advising.
This is a non-tenured teaching position, where the core focus will be on course development (traditional and online), teaching, student support, and administrative tasks such as student support, admissions, and committee participation. The teaching component (85-90%) includes 6 class sections (30 – 40 students each) per year with summers as a potential option. The administrative component varies with need and ranges from 10 – 15%.
Professor of Physics
University of Wisconsin-Madison, Madison, WI
Deadline: 2024-12-31 | Apply
Details
The Department of Physics at the University of Wisconsin-Madison invites applications for an Assistant Professor, Associate Professor, or Full Professor (tenure track) position in the area of artificial intelligence (AI) and machine learning (ML) applied to experimental physics. We encourage applicants who are conducting relevant AI/ML research for enabling new discoveries in fundamental physics using large data sets, innovative computational technologies, and software methodologies.Tenure-track AI Opening
University of Rochester, Rochester, NY
Deadline: 2025-01-01 | Apply
Details
The University of Rochester’s Department of Computer Science seeks to hire an outstanding early-career candidate in the area of Artificial Intelligence.Specifically, we are looking to hire a tenure-track Assistant Professor in any of the following areas:
1. Learning Theory, especially related to deep learning,
2. Machine Learning Systems (ML Ops, memory efficient training techniques, distributed model training methods with GPUs/accelerators, etc.), or
3. Deep reinforcement learning.
Postdoc Opportunities
Postdoctoral Fellow in Geometric Machine Learning
Harvard John A. Paulson School of Engineering and Applied Sciences
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Details
A postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences.Research Fellow positions - Data-Assimilation and Generative Modeling
Department of Statistics & Data Science at the National University of Singapore (NUS)
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Details
Two Postdoctoral Research Fellow positions are available in the Department of Statistics & Data Science at the National University of Singapore (NUS). These positions are offered on a two-year contract basis, with the possibility of renewal subject to review.Postdoctoral Research Associate in AI & Theoretical Physics or Applied Maths
University of Cambridge
Deadline: 2025-01-05 | Apply
Details
Applications are invited for multiple positions at both Research Associate and Senior Research Associate level as Mathematical-AI-Researchers (postdoctoral positions) in the Department of Applied Mathematics and Theoretical Physics as part of the new Infosys-Cambridge AI Lab to work at the interface of science and machine learning. The AI Lab has been created to facilitate reserch in the following themes: agentic AI (multi-agent systems, RL), theoretical machine learning, symbolic AI, and simulation-based approaches. The goal of the AI Lab is to drive scientific discoveries through automation, and to build a mathematical understanding of machine learning using methods from theoretical physics that have wide application beyond science. To facilitate these advances, we seek a talented, promising, and diverse group of researchers with a completed (or near completed) PhD in physics, machine learning or applied mathematics or related fields. Your role as Mathematical-AI-Researcher is to develop and conduct individual and collaborative research within one or more of the themes listed above and to identify and pursue synergies in an interdisciplinary context. You must be able to communicate material of a technical nature beyond your immediate scientific field (e.g. to policymakers or industry leaders) and to enable discussion of real-world applications.Postdoctoral Fellowships in the Physics of Learning
The Department of Physics and Astronomy at Johns Hopkins University, Baltimore, Maryland
Deadline: 2025-01-06 | Apply
Details
The department of Physics and Astronomy at Johns Hopkins University invites applications for (i) multiple independent postdoctoral fellowships and (ii) PhD students to work on the theoretical foundations of (Machine) Learning. Outstanding candidates will be selected to join the Physics of Learning research group led by profs Brice Ménard and Matthieu Wyart. This group will significantly expand in the next couple of years, with the addition of several new faculty members and their respective associates.Research on the theoretical foundations of Learning is highly synergistic. Our members interact with colleagues in the departments of cognitive & neuroscience, computer science and applied mathematics and statistics. This research program also benefits from Johns Hopkins’ major AI initiative, with the addition of new AI faculty across multiple departments and the creation of a new Data Science and AI Institute.
Humboldt Postdoctoral Fellowships with the Collaborative Artificial Intelligence (CAI) group
The University of Stuttgart, Stuttgart, Germany
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Details
The CAI group (https://collaborative-ai.org/) conducts fundamental research towards collaborative artificial intelligence at the intersection of multimodal machine learning, computational cognitive modelling, computer vision, and human-machine interaction. We have a strong presence in leading conferences in these research fields and, as such, are among the few truly interdisciplinary groups in Germany and Europe. We are highly visible internationally, and publications from the group are frequently distinguished with best paper awards. So far, out of 14 PhD and PostDoc alumni, seven have assumed faculty positions at leading institutions worldwide, several others have jointed industrial research labs. Close links exist to the International Max Planck Research School for Intelligent Systems (IMPRS-IS) and the local Max Planck Institute, the ELLIS Unit Stuttgart, the Centre for Bionic Intelligence Tübingen Stuttgart (BITS), as well as several large-scale research projects within the University of Stuttgart.Postdoctoral Fellowships in Deep Learning
NYU Shanghai, Shanghai, China
Deadline: 2025-1-31 | Apply
Details
NYU Leonard Stern School of Business and NYU Shanghai are excited to announce an open call for Postdoctoral Fellowship applications. The position may start in Spring or Fall 2025 and will be under the supervision of Profs. Bruno Abrahao (NYU Shanghai) and João Sedoc (NYU Stern).Post-doctoral assistant department Data Analysis and Mathematical Modelling
Ghent University, Ghent, Belgium
Deadline: 2024-11-19 | Apply
Details
At least 70% of your assignment will be spent on academic research in the field of machine learning. The BioML research group of the Department of Data Analysis and Mathematical Modelling focusses on the development of machine learning methods for the life sciences. Specific research areas of interest are multi-target prediction, sequence learning, time series analysis, uncertainty quantification and probabilistic models. In terms of applications the focus is on analyzing “omics” data (genomics, transcriptomics, proteomics, etc.).Other Academic Opportunities
Research Scientist
The University of Chicago, Chicago, Illinois
Deadline: 2024-12-22 | Apply
Details
AI for Climate (AICE), a program of the Institute for Climate and Sustainable Growth and the Data Science Institute, aims to accelerate and transform climate research with a focus on both scientific advances and societal impacts. AICE and Climate Extremes Theory and Data (CeTD) group invite applications for the position of Research Scientist to work with Prof. Pedram Hassanzadeh on advancing AI weather forecasting across scales, from short- and medium-range to subseasonal-to-seasonal (S2S) predictions. The researcher will closely collaborate with a growing multidisciplinary team, including Profs. Michael Kremer (Economics) and Amir Jina (Public Policy), focused on human-centered weather forecasts, and in conjunction with the international efforts at the Development Innovation Lab (DIL). The appointment will be for up to three years, with the possibility of extending it by one more year if necessary to complete the project. The expected start date is between January 1st and April 1st, 2025.Industry Opportunities
Summer 2025 Internship Opportunities
Toyota Research Institute, Multiple Locations
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Details
TRI envisions a future where Toyota products dramatically improve the quality of life for individuals and society. To achieve this vision, TRI’s Mission is to create new tools and capabilities through our research in energy & materials, human-centered AI, human interactive driving, machine learning, and robotics.Research Scientist Positions (Verification, Robustness)
Safe Intelligence, London, England
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Details
Safe Intelligence is a deep-tech, venture-backed spin-out from Imperial College London building solutions to formally verify the correctness of ML models and improve their robustness against vulnerabilities. Our mission is to develop state-of-the-art research and products that make AI safe and secure for society as a whole.We seek outstanding research scientists who share our passion for reliable AI to enable ML adoption in society-critical applications, including autonomous transportation, finance, robotics, medical imaging, and edge computing.
As a Research Scientist, you will conduct research aligning with the company mission, particularly on ML verification technology and certified learning. Safe Intelligence Research Scientists regularly share their results with the broader community by publishing in top conferences, and similar contributions will be welcomed. We are also passionate about enabling users to deploy ML models safely. A successful Research Scientist will also occasionally interact with users to capture requirements, share capabilities, and feed these to the product team for future iterations.
Joining Safe Intelligence is an opportunity to shape the emerging AI revolution by making it safer and more reliable for everyone.
Responsibilities:
As a Safe Intelligence Research Scientist, you will:
-Develop research on state-of-the-art methods in ML verification and robust learning, also in collaboration with others on the team and the wider community.
-Contribute to mapping out and planning the key research objectives for the company based on existing and emerging product capabilities and strategic objectives.
-Contribute to establishing a culture of high organisational performance.
Technical Requirements:
-Advanced knowledge in deep learning, verification for machine learning, or certified learning.
-Solid experience in training NNs or DTs.
-Solid experience in programming, including Python, particularly in the context of large codebases.
-Good communication skills.
-The ability to collaborate effectively across multiple functional teams.
As a team, we are:
-Passionate about delivering solutions to make AI safer for customers and society.
-Deeply technical and constantly in a state of learning.
-Committed to communicating clearly and efficiently to several audiences, including developers, clients, researchers, partners, and executives.
-Fearless in getting 'hands-on' with technology and execution.
-Comfortable with ambiguity with a drive for clarity.
-Honest, straightforward, and caring about each other’s well-being.
Benefits:
Competitive compensation. Safe Intelligence provides competitive compensation based on role and candidate experience. We are committed to discussing career progress, and the overall package will always be entirely transparent.
In addition, company benefits for all roles include:
-Stock option benefits.
-Mentoring, learning, and development allowance.
-Regular team social and work events.
-Flexible and generous holidays. We work hard and encourage everyone to take time off to recharge and enjoy other aspects of our lives.
Qualifications:
Minimum qualifications:
-Defended or about to defend a graduate degree in ML verification or ML robustness.
-Evidence of top academic publications.
Preferred qualifications:
-Experience in verification or advanced ML environment.
-Experience with complex codebases.
-Excellent communication, problem-solving, and judgement skills.
-Ability to create effective relationships and collaborate internally and externally effectively.
-Excellent analytical capabilities.
Location & Office Culture:
Safe Intelligence is based in London, UK, and we’re focused on building the initial team here. We highly value the ability to work flexibly and remotely at times, but we also have a strong belief that regular in-office interactions make for a much more fulfilling and productive work experience.
Our company culture combines optimism for the future (hard problems can be solved with the right effort), speed of iteration (the best ideas come from many ideas tested), and rigour in what matters (correctness and precision are critical for safety).
Application:
Please send CV and a short statement of your interest in the position to:
join@safeintelligence.ai
http://www.safeintelligence.ai
Come and join us to add your skills and passion to the future of Safe Artificial Intelligence!