Sort by
Refine Your Search
-
Category
-
Country
-
Program
-
Employer
- Oak Ridge National Laboratory
- Harvard University
- EPFL
- Aarhus University
- Argonne
- Earlham Institute
- Forschungszentrum Jülich
- Helmholtz Association of German Research Centres
- King's College London
- SUNY University at Buffalo
- Stanford University
- Technical University of Munich
- The University of Arizona
- University of California
- University of Oslo
- Yale University
- ;
- AALTO UNIVERSITY
- Baylor College of Medicine
- City of Hope
- Dana-Farber Cancer Institute (DFCI)
- Florida Atlantic University
- Georgia Southern University
- Great Bay University
- Hong Kong Polytechnic University
- INSA Rouen Normandie
- Istituto Italiano di Tecnologia
- Lehigh University
- MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE
- Max Planck Institute for Gravitational Physics, Potsdam-Golm
- Mohamed bin Zayed University of Artificial Intelligence
- NTNU Norwegian University of Science and Technology
- Northeastern University
- Oden Institute for Computational Engineering and Sciences
- Pennsylvania State University
- Rutgers University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Saarland University
- Sandia National Laboratories
- SciLifeLab
- Stony Brook University
- Texas A&M University
- Toyota Technological Institute
- University of California, Los Angeles
- University of Florida
- University of Idaho
- University of Lund
- University of Maryland, Baltimore
- University of Nevada, Reno
- University of Texas Rio Grande Valley
- University of Waterloo
- Uppsala universitet
- Zintellect
- 43 more »
- « less
-
Field
-
for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure including LUMI
-
with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
-
-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
-
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
-
with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
-
heat transfer processes Use of advanced numerical methods (CFD, LBM, hybrid models) Utilization of high-performance computing (HPC, GPU) Analysis and validation of numerical results Optimization
-
/ coarse- grained approaches) Experience with enhanced sampling techniques; computational biophysics/chemistry Usage of high-performance computing clusters, preferably GPU-based computing Proficiency in
-
, or population genetics Deep learning for sequence, EHR, or imaging data High-performance and GPU computing environments Excellent candidates from adjacent quantitative fields are encouraged to apply. The Research
-
have access to substantial AI compute, including in-house state-of-the-art H200 GPU servers, alongside further capacity through the Norwich Data Centre and access to national-scale AI compute through