Sort by
Refine Your Search
-
Listed
-
Employer
- Northeastern University
- Oak Ridge National Laboratory
- University of California
- University of Washington
- Brookhaven Lab
- Brookhaven National Laboratory
- Lawrence Berkeley National Laboratory
- The University of North Carolina at Chapel Hill
- University of California, Merced
- University of North Carolina at Chapel Hill
- University of Utah
- Washington University in St. Louis
- 2 more »
- « less
-
Field
-
programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
-
The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 12 days ago
and Experience: Distributed parallel training and parameter-efficient tuning. Familiarity with multi-modal foundation models, HITL techniques, and prompt engineering. Experience with LLM fine-tuning
-
programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
-
software for multi-arch environments Development in high-performance computing (HPC) or distributed systems Strong understanding of Linux toolchains, build systems (CMake), and debugging tools Parallel
-
programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
-
Mathematics, or a related field, awarded within the last five years Programming experience in one or more of Python, C++, Fortran, or Julia Knowledge of high-performance and parallel computing Experience
-
implementing, optimizing, or integrating quantum libraries such as Itensor, CUDA-Q, Qiskit, or PennyLane. Experience debugging and profiling distributed-memory parallel applications. Knowledge of Git and modern
-
. Experience implementing, optimizing, or integrating quantum libraries such as Itensor, CUDA-Q, Qiskit, or PennyLane. Experience debugging and profiling distributed-memory parallel applications. Knowledge
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
-reviewed publications in relevant fields Strong problem-solving skills and the ability to work in a collaborative environment. Preferred Qualifications, Competencies, and Experience Distributed parallel
-
distributed systems techniques. Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and parallel computing. Demonstrated hands-on experience and