Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Oak Ridge National Laboratory
- EPFL
- Argonne
- Forschungszentrum Jülich
- Harvard University
- Helmholtz Association of German Research Centres
- KTH Royal Institute of Technology
- NEW YORK UNIVERSITY ABU DHABI
- SciLifeLab
- Stanford University
- Technical University of Munich
- University of Copenhagen
- University of South Carolina
- Yale University
- ;
- Baylor College of Medicine
- CNRS
- ETH Zürich
- Eindhoven University of Technology (TU/e)
- Fundació per a la Universitat Oberta de Catalunya
- Ghent University
- Great Bay University
- INSA Rouen Normandie
- Indiana University
- Inria, the French national research institute for the digital sciences
- Istituto Italiano di Tecnologia
- King's College London
- Lehigh University
- MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE
- Mohamed bin Zayed University of Artificial Intelligence
- National Aeronautics and Space Administration (NASA)
- Northeastern University
- Pennsylvania State University
- Rutgers University
- SUNY University at Buffalo
- SUNY at Buffalo
- Saarland University
- Sandia National Laboratories
- Singapore-MIT Alliance for Research and Technology
- Stony Brook University
- Texas A&M University
- The University of Arizona
- Toyota Technological Institute
- University of Amsterdam (UvA)
- University of California
- University of California, Los Angeles
- University of Lund
- University of Minnesota
- University of New Hampshire
- University of North Carolina at Chapel Hill
- University of Texas at Arlington
- University of Utah
- Utrecht University
- 43 more »
- « less
-
Field
-
University of California, Los Angeles | Los Angeles, California | United States | about 20 hours ago
Nextflow or Snakemake, version control such as Git, and reproducible computational environments is preferred. Familiarity with GPU-accelerated genomics, high-performance computing, or cloud-based analysis
-
-learning architectures for sequential data (e.g., Transformers, graph neural networks, state-space models). Experience with OpenCV, GPU-accelerated inference, Docker, and modern software engineering
-
with AMD MI300A GPU+CPU. 2. Perform benchmarking studies to enhance scalability and achieve high node-level efficiency, surpassing existing AMR frameworks. 3. Contribute to communication optimizations
-
establish a research profile. Develop and execute innovative research projects. Develop, train, and evaluate modern machine-learning models on GPU/HPC infrastructure. Integrate AI methods with scientific
-
software (e.g., Paraview). Preferred Qualifications: Exposure to developing agentic workflows. Code development using Git repositories, GPU computing. Development of agentic workflows for scientific
-
, 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
-
large GPU clusters on cryoSTEM datasets in the multi-terabyte range. This position plays a pivotal role in supporting ongoing, high-impact research programs within our lab. The successful candidate will
-
foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
-
). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI
-
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