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Los Alamos National Laboratory

Just Landed

Fermilab Research Associate in AI for Science Fermilab in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Dec 30, 2026

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Country

United States

University

Los Alamos National Laboratory

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Keywords

Computer Science
Deep Learning
Mathematics
Statistical Analysis
Artificial Intelligence
Astronomy
High-energy Physics
Cosmology
Computational Science
Neutrino Physics
Uncertainty Analysis
Domain Adaptation
Collider Physics
Interpretability
Physics
ML

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About this position

Fermilab’s Computational Science and Artificial Intelligence Directorate is offering a postdoctoral research position in AI for science within Dr. Aleksandra Ciprijanovic’s research group. The successful researcher will join a team working at the intersection of deep learning, cosmology, and high-energy physics, contributing to both methodological AI research and applications in science.

The project centers on developing and studying machine-learning methods for scientific discovery, with a particular emphasis on graph neural networks for cosmology, neutrino physics, and collider physics. The role also includes work on domain adaptation and model robustness, uncertainty quantification, and model interpretability. In addition to these core themes, the position welcomes experience with broader advanced deep learning approaches such as simulation-based inference, normalizing flows, flow matching, diffusion models, transformers, and foundation models.

The researcher will be embedded in a collaborative environment at Fermilab, a major U.S. national laboratory known for large-scale research in particle physics and computational science. The post is tied to Dr. Ciprijanovic’s group, offering an opportunity to contribute to research that bridges AI methodology with questions in cosmology and high-energy physics.

Funding details

Available

What's required

A PhD in astrophysics, physics, computer science, or a related field is required. Applicants should have a strong background in AI/ML such as PyTorch or TensorFlow, collaborative software development experience, research experience in cosmology/astrophysics or alternatively neutrino, collider physics, or computer science, demonstrated experience in scientific computing and data analysis, excellent collaboration and communication skills, publications in leading (astro)physics and/or AI journals or conferences, and an interest in mentoring junior scientists.

How to apply

Apply through the AcademicJobsOnline application page. Submit a CV with publications, a cover letter, a research statement of up to 3 pages, and three reference letters. Complete applications received by the deadline will receive full consideration.

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