Postdoktor inom probabilistiska metoder för foundation och world modeller
Core
Developing probabilistic methods for foundation and world models to make them uncertainty-aware, calibrated, and robust for scientific decision-making.
Role type
Postdoctoral researcher (Scientific Machine Learning)
Builds
Open-source software for data-driven science and high-impact research papers.
Domain
AI/ML research, computational science, life sciences (microscopy, drug development, precision medicine)
Deliverable
research
Required skills
Deep learning, Python, PyTorch or JAX, probabilistic modeling, uncertainty quantification, generative models, simulation-based inference
Preferred skills
Bayesian methods, multimodal models, large-scale GPU training, open-source development, teaching experience
Technologies
PyTorch, JAX, Python
Responsibilities
Conduct research, publish papers, present at conferences, contribute to open-source software, supervise students
Seniority
Postdoctoral researcher