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Eilam Gross

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Postdoctoral Position in Machine Learning for Collider Physics Weizmann Institute of Science in Israel

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available
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Country

Israel

University

Weizmann Institute of Science

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Keywords

Computer Science
Experimental Physics
Deep Learning
Artificial Intelligence
Particle Physics
High-energy Physics
Generative Modeling
Collider Physics
Data Reconstruction
Statistics
Physics
Machine learning

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About this position

Postdoctoral Research Position in Machine Learning for Collider Physics at the Weizmann Institute of Science.

The group led by Eilam Gross is recruiting an outstanding postdoctoral researcher to work at the intersection of machine learning and experimental particle physics. The research aims to develop next-generation AI methods for collider experiments, with applications to the ATLAS experiment at CERN and broader high-energy physics problems.

Current topics include hypergraph and transformer-based particle reconstruction for the High-Luminosity LHC, fast surrogate models for detector simulation and reconstruction, multimodal foundation models for detector data, and new ML methods with applications beyond particle physics.

This is a research-intensive postdoc with substantial intellectual freedom, opportunities to lead original ideas, collaborate with students and colleagues, and contribute to both physics and machine learning publications. The position also includes access to local GPU resources, close collaboration with ATLAS, and the possibility of extended visits to CERN.

Eligibility: applicants should hold a PhD in particle physics, astrophysics, computer science, or a related field. Strong machine learning experience is expected; PyTorch is preferred. Experience with detector reconstruction, simulation, generative models, or transformers is especially welcome.

How to apply: follow the full details and application instructions in the linked job post. The post points to an InspireHEP job listing for the application information.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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