Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Oak Ridge National Laboratory
- The University of Chicago
- National Renewable Energy Laboratory NREL
- University of Delaware
- University of Michigan
- CNRS
- Chalmers University of Technology
- Cornell University
- George Mason University
- Harvard University
- NIST
- Nanyang Technological University
- Northeastern University
- Purdue University
- Rutgers
- Rutgers University
- St Jude Children's Research Hospital
- Technical University of Denmark
- The University of Iowa
- University of Colorado
- University of Louisville
- University of Nevada Las Vegas
- University of Notre Dame
- University of Tennessee at Chattanooga
- University of Washington
- 15 more »
- « less
-
Field
-
to closely collaborate with CS faculty members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience
-
. Keywords Image processing; Machine learning, Computer vision; Statistical methods; Parallel and distributed computing; Software engineering; Standards; Eligibility citizenship Open to U.S. citizens level
-
: Experience with CUDA programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high
-
optimization, intelligent runtime systems, code generation and transformation, HPC, parallel and distributed computing, compiler infrastructures, heterogeneous systems, and autonomous system optimization
-
, and reproducible code development skills; distributed or parallel computing is a plus. Experience designing and executing field experiments in urban or environmental settings, with willingness to
-
across Linux environments, programming and scripting languages, job scheduling, scientific applications, optimized compilers, mathematical libraries and algorithms, and distributed and parallel file
-
systems and servers. Documenting system administration procedures for routine and complex tasks. Technical Environment: Linux build automation in a large, distributed computing environment with Puppet
-
developing and managing automated and parallel scientific workflows , including task execution systems, dependency management, and pipeline execution on distributed computing resources. Experience with HPC
-
benchmarking of parallel and distributed computing systems and of the workflow systems that run on them. Familiarity with the FAIR data and research software principles, and with producing AI-ready
-
, Electrical Engineering, Mathematics, or a closely related field. Strong programming proficiency in Python and C or C++. Experience with parallel and distributed computing using technologies such as MPI