Postdoktor inom simuleringsbaserad inferens för partikelfysik
Core
Developing simulation-based inference (SBI) methods using neural networks to search for dark matter and new physics signals at the Large Hadron Collider.
Role type
Postdoctoral researcher in scientific machine learning
Builds
Robust SBI methods and open-source software for high-dimensional collision data analysis
Domain
Particle physics and computational science
Deliverable
production ML models
Required skills
deep generative models, probabilistic modeling, Python, PyTorch or JAX, high-dimensional data analysis, neural network training
Preferred skills
simulation-based inference, flow matching, diffusion models, particle physics (MadGraph, Pythia, Delphes), GPU/HPC training, open-source development
Technologies
PyTorch, JAX, NAISS, GPU clusters
Responsibilities
Method development, large-scale computation experiments, publishing, presenting at international conferences, contributing to open-source software, mentoring students
Seniority
Postdoctoral researcher