Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Oak Ridge National Laboratory
- EPFL
- Argonne
- Forschungszentrum Jülich
- Helmholtz Association of German Research Centres
- King's College London
- Stanford University
- Technical University of Munich
- The University of Arizona
- Yale University
- ;
- AALTO UNIVERSITY
- Aarhus University
- Baylor College of Medicine
- Great Bay University
- Harvard 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
- Northeastern University
- Pennsylvania State University
- SUNY University at Buffalo
- Saarland University
- Sandia National Laboratories
- SciLifeLab
- Stony Brook University
- Texas A&M University
- Toyota Technological Institute
- University of California
- University of California, Los Angeles
- University of Florida
- University of Lund
- Uppsala universitet
- 26 more »
- « less
-
Field
-
, 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
-
Python and experience with GPU processing of large-scale datasets. Excellent written and oral communication skills in English. We also value applications from people with the following experience
-
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
-
scientific programming in Python and experience with GPU processing of large-scale datasets. Experience with inverse problems and 3D reconstruction methods for tomography, laminography, or a closely related
-
Python and experience with GPU processing of large-scale datasets. Excellent written and oral communication skills in English. We also value applications from people with the following experience
-
-performance computing, GPU acceleration, automated benchmarking or large-scale numerical workflows. Evidence of self-motivated contributing to collaborative research outputs, open-source software, preprints
-
and hundreds million) Skills in AI-enabled and GPU-based calculations are welcome Good communication skills and the ability to work in a team environment Ability to work independently to solve critical
-
trajectory optimization, nonlinear programming, or genetic algorithms. High-performance computing (HPC), parallel numerical workflows, or GPU-accelerated model execution. Terms of Appointment This is a full
-
, microfluidics, laboratory automation, and GPU computing infrastructure. The opportunity to develop AI methods and scientific software that are directly deployed on cutting-edge experimental platforms. Vacation
-
scientific domains. Preferred Experience: Strong candidates may also have experience with: Large-scale neuroimaging datasets. GPU-based model training and distributed computing. Brain connectivity modeling