Sort by
Refine Your Search
-
Listed
-
Employer
- Argonne
- Oak Ridge National Laboratory
- University of Texas at Tyler
- Brookhaven Lab
- Brookhaven National Laboratory
- Carnegie Mellon University
- Embry-Riddle Aeronautical University
- Genentech
- Georgia Institute of Technology
- Indiana University
- Johns Hopkins University
- Michigan Technological University
- Nature Careers
- Northeastern University
- Northwestern University
- Purdue University
- Rutgers University
- The University of Memphis
- University of California Irvine
- University of California, Merced
- University of Minnesota
- University of Nevada Las Vegas
- University of North Carolina at Chapel Hill
- University of North Texas at Dallas
- University of Virginia
- Virginia Tech
- 16 more »
- « less
-
Field
-
computing AI on High-Performance Computing (HPC) cluster. Examples on areas of research interest include but are not limited to: Vision transformers. AI foundation models. Computing and energy-efficient
-
and risk assessment modeling. • Prior experience with CCUS research projects. • Familiarity with high-performance computing (HPC) and parallel computing techniques. Required Knowledge, Skills, and/or
-
software and high-performance computing (HPC). These include particle and gravitational physics. -On the data analysis side, the group designs novel statistical methods for particle physics and astrophysics
-
-series data of astronomical transients, including gravitational wave data analysis. Experience with high-performance or high throughput computing (HPC/HTC). The initial appointment is for 1 year. It is
-
modeling. Perform predictive modeling using high-performance computing (HPC) infrastructure. Validate computational predictions by collaborating with experimental groups conducting reverse genetics studies
-
discipline. Demonstrated hands-on experience and understanding of developing and applying HPC algorithms to sparse numerical, scientific and ML models. Demonstrated research experience with AI and ML
-
-performance computing (HPC) environment Perform data analysis and visualization Perform machine learning and inverse design techniques Train and supervise masters and doctoral students Coordinate research with
-
computing (HPC) development of SeA (in collaboration with the DiStasio research group at Cornell University) and the broader QE package. We also expect this position to offer many other collaborative
-
-house CFD software packages. (3) Designing and developing CFD sub-models for application to a broad range of CFD problems. (4) Using high-performance computing (HPC) to accelerate complex, large-scale
-
wind tunnels such a temperature/pressure sensitive paints, infrared thermography, PLIF, FLDI etc. • Proficiency in Python • Experience running simulations with high performance computing (HPC) resources