Sort by
Refine Your Search
-
Country
-
Program
-
Employer
- EPFL
- Oak Ridge National Laboratory
- Aarhus University
- King's College London
- Stanford University
- University of Oslo
- Argonne
- Great Bay University
- INSA Rouen Normandie
- NTNU Norwegian University of Science and Technology
- Saarland University
- SciLifeLab
- Stony Brook University
- The University of Arizona
- University of California
- University of Waterloo
- Uppsala universitet
- Yale University
- 8 more »
- « less
-
Field
-
extracting transport properties from molecular dynamics trajectories. ● Experience with GPU-accelerated machine learning frameworks (for example CUDA, PyTorch, or GPU-enabled LAMMPS). ● Experience
-
working conditions? We welcome you to apply for a postdoc position at Uppsala University. Uppsala University is a comprehensive research-intensive university with a strong international standing. Our
-
GPU infrastructure. This Postdoc position is part of the eSSENCE graduate school in data-intensive science. The school addresses the challenge of data-intensive science both from the foundational
-
for career development Access to high-performance computational resources (with GPUs) A collaborative environment across research fields, including plant biology, quantitative genetics, and population genetics
-
-to-end GPU timing; document limitations and extrapolation behavior. Implement, test, document, and maintain open-source Python/JAX research software; collaborate with researchers to connect trained models
-
Postdoc Positions Application Deadline 15 Aug 2026 - 09:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Sep 2026 Is the job funded
-
Researcher (R3) Positions Postdoc Positions Application Deadline 15 Aug 2026 - 23:59 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Full-time Hours Per Week 39,5 Offer Starting Date 1
-
, validation, calibration, and inference. Working with large, longitudinal, structured and unstructured datasets in Linux and high-performance or GPU-accelerated computing environments. Applying rigorous methods
-
imaging of dynamic processes, while the companion position focuses on high-throughput imaging of static structural defects . Each postdoc will lead their own independent research direction, with
-
or OpenMP. Experience in heterogeneous programming (i.e., GPU programming) and/or developing, debugging, and profiling massively parallel codes. Experience with using high performance computing for lattice