Fermilab Research Associate

Fermilab Computational Science and Artificial Intelligence Directorate Batavia, United States

About the position

Position Description

Fermilab is excited to announce one postdoctoral researcher position in AI for science with Dr. Aleksandra Ciprijanovic (alexciprijanovic.com) and her research group! The successful candidate will join a team working at the intersection of deep learning, cosmology, and high-energy physics, with opportunities to contribute to both methodological AI research and applications in science.

This is a term position for 2 years, renewable for the third year, depending on performance and interest.

A particular focus of the project will be on:

  • Graph Neural Networks for cosmology, neutrino, and/or collider physics,
  • Domain adaptation / model robustness,
  • Uncertainty quantification,
  • Model interpretability.

Experience with other deep learning methods, such as Simulation-Based Inference (SBI) with Normalizing Flows or Flow Matching, Diffusion Models, Transformers, or Foundation Models is also a plus.

Skills and Attributes for Success:

  • PhD in astrophysics, physics, computer science, or related fields
  • Strong background in AI/ML (e.g., PyTorch, TensorFlow) and collaborative software development
  • 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/conferences
  • Excellent oral and written communication skills
  • Experience or interest in mentoring junior scientists

Please see further job details and apply at: https://academicjobsonline.org/ajo/jobs/33283

A full application will include:

1. CV with a list of publications

2. Cover letter

3. A brief statement of up to 3 pages of your research interests

4. Three letters of reference

Complete applications received by December 30, 2026 (11:59pm CST) will receive full consideration.

Questions can be directed to Aleksandra Ciprijanovic (aleksand@fnal.gov).

This listing was collected from a public source and is reproduced here for information only. Always confirm the details on the original posting before applying.
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