Sort by
Refine Your Search
-
Listed
-
Employer
- Oak Ridge National Laboratory
- Northeastern University
- Princeton University
- Argonne
- Medical College of Wisconsin
- University of California
- University of Kansas
- University of Washington
- Brookhaven Lab
- Brookhaven National Laboratory
- Brown University
- Florida International University
- Fred Hutchinson Cancer Center
- George Washington University
- Lawrence Berkeley National Laboratory
- Massachusetts Institute of Technology
- Massachusetts Institute of Technology (MIT)
- Michigan Technological University
- Nature Careers
- The University of Arizona
- University of California Davis
- University of California Los Angeles
- University of California, Los Angeles
- University of California, Merced
- University of Minnesota
- University of Oklahoma
- University of Southern California
- University of Southern California (USC)
- University of Texas at Austin
- Virginia Tech
- Washington State University
- Washington University in St. Louis
- 22 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
-
with environment, safety, health and quality program requirements. Maintain strong dedication to the implementation and perpetuation of values and ethics. Deliver ORNL’s mission by aligning behaviors
-
dynamics (DNS, LES, or RANS) and/or high-performance computing (MPI, GPU, or parallel solvers), as demonstrated by application materials. Evidence of peer-reviewed publications in fluid dynamics, turbulence
-
University of Southern California (USC) | Los Angeles, California | United States | about 13 hours ago
, AI, Data Science, Statistics, or related.Strong skills in machine learning and deep learning, with a fundamental understanding of LLMs.Proficiency in Python programming and major ML/DL
-
multiphase flow in porous media. 80% - Applying numerical and analytical infiltration models to quantify groundwater recharge potential under varying hydrogeologic conditions. In parallel, the researcher will
-
computational fluid dynamics (DNS, LES, or RANS) and/or high-performance computing (MPI, GPU, or parallel solvers), as demonstrated by application materials. Evidence of peer-reviewed publications in fluid
-
research program investigates the microenvironment/niche of human limbal stem cells to elucidate those factors that govern the fate of limbal stem cells and pathophysiology of limbal stem cell deficiency
-
smoothly by managing reagents and supplies and performing genomic assays and assisting with long read Nanopore sequencing, functional genomics, RNA IP, RNA probe synthesis and Massively Parallel reporter
-
leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
-
and/or 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