Fermilab Research Associate

Fermilab; City of Batavia (NY); On-site; USD 65,000 - 90,000; Part time

Job summary

Fermilab invites applications for a postdoctoral researcher position in AI for science led by Dr. Aleksandra Ciprijanovic. The successful candidate will explore deep learning methods for cosmology and high-energy physics, contributing to both methodological AI work and scientific applications.

The appointment is a two-year term with potential renewal for a third, contingent on performance and interests. Ideal candidates will demonstrate strong collaboration, publication history, and mentoring

Qualifications

• PhD in astrophysics, physics, computer science, or related field.
• Strong background in AI/ML with practical software development experience.
• Proven research track record in cosmology/astrophysics or related areas.

Responsibilities

• Conduct advanced AI/ML research at the intersection of cosmology and high-energy physics.
• Develop and evaluate models (GNNs, uncertainty quantification, domain adaptation) for scientific data.
• Contribute to method development and practical applications in science.

Skills

AI/ML research & collaboration

Mentoring juniors

Publications in astro/AI

Education

PhD in astrophysics/physics/CS

Tools

PyTorch

TensorFlow

Job description

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

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

Questions can be directed to Aleksandra Ciprijanovic ([e-mail]).