Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
-
contact, as identified by AFRL through recent past efforts. This includes the implementation of relevant algorithms and solvers for distributed GPU computing within the JAX Python library. Qualifications
-
contact, as identified by AFRL through recent past efforts. This includes the implementation of relevant algorithms and solvers for distributed GPU computing within the JAX Python library. Qualifications
-
, and progression outcomes) and high-end compute (hundreds of NVIDIA H100 GPUs) via Mila and the Digital Research Alliance of Canada, and involves active collaborations with Stanford, Oxford, Google
-
including code design, documentation and testing. Familiarity with optimization methods including Machine Learning (ML) techniques. Any experience with computations on GPUs. Working knowledge of Linux command
-
reasoning or tool-augmented LLMs, RL (RLHF/RLAIF/online RL), or foundation models for science, Software engineering skills (Python) and experience with modern DL stacks (PyTorch) and multi-GPU training
-
with GPU-accelerated computation and high-dimensional data analysis. Enthusiasm for applying AI innovations to real biological and medical challenges. Required Application Materials: Cover letter
-
Preferred Qualifications: Experience in thermos-fluids in porous media. Experience in High-Performance Computing (HPC) on CPU or GPU platforms. Experience in mentoring of graduate and undergraduate students.
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 23 days ago
of data scientists/clinicians and working with unique datasets from multiple academic medical centers (e.g. UNC, UCSF, Mayo Clinic, Memorial Sloan Kettering, etc). Lab dedicated GPU workstations/servers and
-
conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed proceedings. Knowledge of systems