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
Faculty Opportunities
Postdoc Opportunities
Postdoctoral researchers at any of the partner institutions may collaborate with IAIFI researchers to become a Junior Investigator.
IAIFI Fellow
IAIFI/MIT
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IAIFI seeks a talented, promising, and diverse group of researchers at an early stage of their careers to join the IAIFI Fellowship program. The role of an IAIFI Fellow is to spark vital interdisciplinary, multi-investigator, multi-subfield collaborations across the primary IAIFI thrusts of theoretical physics, experimental physics, and foundational AI. Such collaborations have immense power to generate new ideas and approaches in both physics and AI, to facilitate abstracting physics challenges beyond their native domains to inform the development of cutting-edge AI tools, and to instill a common language across disciplines. Our program aims to appoint new postdoctoral IAIFI Fellows each academic year, for a three-year fellowship term each.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.
Academic Opportunities
Faculty Opportunities
Assistant Professor of Physics and Statistical & Data Sciences
Smith College, Northampton, MA
Deadline: 2024-10-04 | Apply
Details
The Department of Physics and the Program in Statistical and Data Sciences at Smith College invite applications for a joint tenure-track position at the rank of Assistant Professor, to begin July 1, 2025. Details about the Department of Physics and the Program in Statistical and Data Sciences may be found at https://www.smith.edu/academics/physics and https://www.smith.edu/academics/statistics.A Ph.D. in Physics or a closely related field is expected by the time of appointment; additional degrees in statistics, computer science, or data science are welcome but not required. The successful candidate is expected to establish a professional identity in both fields as an important part of their research and teaching activities at Smith. Applicants should be passionate about inclusive teaching and be able to offer substantive research opportunities for undergraduates studying in both fields.
AI Faculty Positions
University of Alberta
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The University of Alberta is conducting a broad hiring initiative to recruit 20+ new faculty members across various disciplines as part of an AI cohort hire. The university is particularly seeking candidates at all levels (Assistant, Associate, and Full Professor) whose home department would be outside of Computer Science or Computer Engineering. Each position comes with a nomination for a Canada CIFAR AI Chair, including generous five-year funding, and the opportunity to join the Alberta Machine Intelligence Institute as a Fellow.Tenure-Track Position in Artificial Intelligence for Science
University of Caen
Deadline: 2024-09-15 | Apply
Details
The University of Caen is seeking a dynamic and innovative researcher to join our faculty as a tenure-track professor in the field of Artificial Intelligence (AI) and Machine Learning (ML) for Science. This position is part of our initiative to become a leading institution in AI for transforming research across a wide range of disciplines. We are looking for candidates with a strong multidisciplinary background at the interface of AI/ML and sciences, and whose research can drive significant advancements in nuclear physics, materials science, or chemical engineering. The successful candidate will be expected to contribute to our endeavour of leveraging AI/ML to make discoveries in these fields and to explore the societal impacts of these technological advancements. For further information, please email Frederic Jurie at frederic.jurie@unicaen.fr, using AI for Science Tenure-Track Position as the email subject.Tenure-track or Tenured Professor in Computer Science and Kempner Institute Investigator
Harvard John A. Paulson School of Engineering and Applied Sciences
Deadline: 2023-12-15 | Apply
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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 or tenured position specializing in Machine Learning and Artificial Intelligence, with an expected start date of July 1, 2024. 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.Open-Rank Faculty Positions in AI/ML
Georgia Tech
Deadline: 2023-11-15 | Apply
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The School of Physics at the Georgia Institute of Technology invites applications for two open-rank tenure-track faculty positions at the interface between machine learning and physics. We anticipate hiring faculty working on advancing machine learning methodology as applied to quantum science, astrophysics, physics of living systems, nonlinear science, soft matter physics or other related areas. The faculty will be part of a new initiative to catalyze machine-learning-driven research in the School of Physics and will benefit from substantial expertise and resources in artificial intelligence and machine learning that already exist in the Colleges of Sciences, Engineering, and Computing. Appointments at senior ranks will be considered for candidates with established and internationally recognized research programs. Candidates are expected to have received a doctorate in Physics or a related discipline and demonstrate a record of advancing the methodology and applications of machine learning in Physics. Successful candidates will have expertise in teaching, scholarship, and/or service.Postdoc Opportunities
PostDoc in biometrics funded by the SMASH MSCA Program
University of Ljubljana, Slovenia
Deadline: 2024-09-16 | Apply
Details
The Faculty of Computer and Information Sciences, University of Ljubljana, Slovenia is looking for a strong candidate to join the Computer Vision Laboratory as a Post-Doctoral fellow to work with Prof. Dr. Peter Peer.Specifically, in problems related to deep learning in computer vision and biometrics applicable to deepfake detection, explainability, synthetic data, and generative AI. The work will be done jointly with the Laboratory for Machine Intelligence (Prof. Dr. Vitomir Štruc).
Upon successfully securing funds the selected PostDoc will be enrolled into the program. The program includes a two-year position, excellent working conditions, access to top infrastructure (including the HPC Vega), substantial research and travel funds and a salary that is significantly higher than local costs of living and comparable to a Slovenian full professor salary.
Interested candidates in joining the program are invited to send the following application documents as one PDF file to peter.peer@fri.uni-lj.si by 16 September 2024:
-Cover letter briefly describing the motivation for the application.
-Detailed CV highlighting experience in computer vision, biometrics, and deep learning including strong prior publications in top SCI journals and conferences with the link to Google Scholar profile.
-One page research proposal in biometrics.
-The names and contact details of at least two referees willing to provide support letters.
Data science and AI expert for Clinical NLP and LMs
Barcelona Supercomputing Center (BSC), Spain
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The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress.The NLP4BIA-BSC is looking for a Postdoctoral Research Engineer with experience in Language Technologies and Deep Learning. The candidate will be involved in technical work related to international projects, being part of a team of researchers working on topics related to multilingual information extraction in the clinical field, including Named-Entity Recognition, Entity Linking and Language Modeling.
The candidate will have the opportunity to advance the state of the art of cross-lingual biomedical NLP methods by working in a multidisciplinary environment alongside linguists, medical experts, and other engineers.
Postdoctoral Research Position in Physics and Machine Learning
University of Caen, France
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We are seeking a highly motivated postdoctoral researcher to join our team working at the intersection of particle physics and machine learning. The ideal candidate will have a strong background in physics, particularly in particle physics, and expertise in machine learning techniques. Project Description: The successful candidate will focus on analyzing and advancing uncertainty estimation methods for neural networks, with a particular emphasis on generative models. The research will aim to develop and experiment with novel algorithms that can provide reliable uncertainty estimates for machine learning models used in high-energy physics simulations. The application context for this research will be the study of neutrinos in the KM3NeT telescopes, specifically focusing on atmospheric neutrino oscillations and the potential existence of sterile neutrinos. Currently, Monte Carlo (MC) simulations are widely used for modeling neutrino observations, providing results with guarantees on data quality but at a high computational cost. The project will explore the potential of replacing these MC simulations in some applications with generative models such as diffusion models or other generative approaches, while addressing the critical question of reliability compared to traditional MC simulations. Key Responsibilities: Conduct a comprehensive literature review on uncertainty estimation in neural networks, focusing on generative models; Propose and experiment with novel algorithms for uncertainty quantification in generative models; Apply developed methods to neutrino physics simulations and compare results with traditional Monte Carlo approaches; Collaborate with physicists and machine learning experts to ensure the relevance and applicability of the developed methods; Present research findings at conferences and prepare manuscripts for publication in peer-reviewed journals. Qualifications: Ph.D. in Physics, Computer Science, or a related field; Background in Monte Carlo simulation, particle physics and machine learning; Experience with generative models and uncertainty quantification techniques; Proficiency in programming languages commonly used in scientific computing and machine learning (e.g., Python, PyTorch, TensorFlow); Excellent communication and collaborative skills; Publication record in relevant fields is highly desirable; This position offers an exciting opportunity to contribute to cutting-edge research at the intersection of fundamental physics and advanced machine learning techniques. The successful candidate will integrate a dynamic interdisciplinary group composed of researchers, AI experts and PhD students from the KM3NeT experimental group at LPC and from GREYC. Access to state-of-the-art computing resources is available locally and at national computing centers. To apply: Please submit your CV, a brief statement of research interests, and contact information for three references to Frederic Jurie (frederic.jurie@unicaen.fr) and Antonin Vacheret (vacheret@lpccaen.in2p3.fr).S. Scott Collis Fellowship in Data Science
Sandia National Laboratories
Deadline: 2024-10-28 | Apply
Details
The S. Scott Collis Fellowship in Data Science at Sandia National Laboratories seeks applicants with a demonstrated background and interest in the interdisciplinary domain of data science to include mathematics, computer science, artificial intelligence, statistics, computer engineering, and related areas. Collis Data Science Fellows work at the junction of cutting-edge data science techniques and Sandia’s national security mission and application space. Examples of relevant data science techniques range from machine learning and deep learning to advanced statistical methods to optimization techniques to methods designed for specialized hardware and beyond. Examples of the scientific and engineering applications relevant to Sandia’s diverse missions include nuclear deterrence and nonproliferation, numerical modeling and scientific simulation, energy systems and power grid, cyber security, operations research, geospatial analysis, neuromorphic computing, and many other national security domains.Machine Learning Postdoc Positions - Manchester
University of Manchester, UK
Deadline: 2024-09-15 | Apply
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Thinking about the next position for your research career? Professor Samuel Kaski is hiring postdocs in his machine learning research group both in Helsinki, Finland and Manchester, UK. Professor Samuel is a Machine Learning Professor operating 50-50 in the UK and Finland. In Finland he leads the Finnish Center for Artificial Intelligence FCAI, and in the UK the Manchester Centre for AI Fundamentals AI-FUN. Professor Samuel's group develops new machine learning methods and study machine learning principles. Keywords include: probabilistic modelling, Bayesian inference, simulation-based inference, multi-agent RL and collaborative AI, sequential decision making and experimental design, active learning, human-in-the-loop learning and user modelling, privacy-preserving learning, Bayesian deep learning, generative models. The group also solves problems of other fields with the methods – and use those problems as test benches when developing the methods. The group has excellent collaborators in drug design, synthetic biology and biodesign, personalized medicine, cognitive science and human-computer interaction. Feel free to contact Professor Samuel Kaski (sami.kaski@gmail.com) for more details; please Cc Ian Evans (ian.evans@manchester.ac.uk). You can learn more at: https://kaski-lab.com/Machine Learning Postdoc Positions - Helsinki
Aalto University, Helsinki
Deadline: 2024-09-15 | Apply
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Thinking about the next position for your research career? Professor Samuel Kaski is hiring postdocs in his machine learning research group both in Helsinki, Finland and Manchester, UK. Professor Samuel is a Machine Learning Professor operating 50-50 in the UK and Finland. In Finland he leads the Finnish Center for Artificial Intelligence FCAI, and in the UK the Manchester Centre for AI Fundamentals AI-FUN. Professor Samuel's group develops new machine learning methods and study machine learning principles. Keywords include: probabilistic modelling, Bayesian inference, simulation-based inference, multi-agent RL and collaborative AI, sequential decision making and experimental design, active learning, human-in-the-loop learning and user modelling, privacy-preserving learning, Bayesian deep learning, generative models. The group also solves problems of other fields with the methods – and use those problems as test benches when developing the methods. The group has excellent collaborators in drug design, synthetic biology and biodesign, personalized medicine, cognitive science and human-computer interaction. Feel free to contact Professor Samuel Kaski (sami.kaski@gmail.com) for more details; please Cc Fang Wang (fang.wang@aalto.fi). You can learn more at: https://kaski-lab.com/Complexity Postdoctoral Fellowships
Santa Fe Institute - New Mexico
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Postdoctoral Fellows spend up to three years in residence at SFI, where they contribute to SFI’s research in the sciences of complexity and are trained to become leaders in interdisciplinary science. As thought leaders who shape the future of science, Postdoctoral Fellows also participate in a unique training program structured to develop leadership skills throughout their three-year residencies and beyond. The Institute provides an opportunity to collaborate with leading researchers worldwide, discretionary and collaborative funds, and a competitive salary with a generous benefit package including paid family leave.Other Academic Opportunities
Industry Opportunities
Senior Machine Learning Software Engineer
The Wikimedia Foundation, Fully Remote
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The Wikimedia Foundation is looking for a Senior Machine Learning Engineer to join a small team spread across UTC -5 to UTC +3 (Eastern Americas, Europe, and Africa) and will report to the Machine Learning Engineering Manager, Ilias Sarantopoulos.As a Senior Machine Learning Engineer, you will be responsible for planning, developing, training, documenting, deploying, and managing production machine learning models. In this role, you will work with product teams, SREs, researchers, and the volunteer community on machine learning models making Wikipedia and similar projects better.
ML Research Engineer
Prune AI, Fully Remote
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At Pruna, we’re on a mission to make AI more efficient to build a better future. While AIs from Big Tech are transforming our societies, for better or for worse, we're levelling the playing field by building tech that makes AI models as accessible and sustainable as possible.As an ML Research Engineer at Pruna AI, you will be instrumental in integrating and optimizing cutting-edge machine learning compression methods. We are looking for talented individuals at all levels of seniority who are passionate about AI and sustainability.
Senior Applied Scientist, Selling Partner Communities (SPC)
Amazon.com Services LLC - Seattle, WA; San Diego, CA; or Arlington, VA
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Amazon is seeking a Senior Applied Scientist to join the Selling Partner Communities (SPC) Science team and lead their multi-year voice of seller Machine Learning projects.This hands-on, pivotal role will take research to production, leveraging NLP, sentiment analysis, LLMs, RAGs, and causal modeling.
ML Engineer Positions
Cusp AI - Amsterdam, Cambridge (UK), Berlin
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