Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- Oak Ridge National Laboratory
- ETH Zurich
- European Space Agency
- McGill University
- The University of Chicago
- Aalborg University
- Blekinge Institute of Technology
- Cornell University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- The University of Alabama
- University of Colorado
- University of Washington
- EPFL
- Harvard University
- Inria, the French national research institute for the digital sciences
- Malmö University
- Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH
- University of Delaware
- University of Glasgow
- University of Louisville
- University of Lund
- University of Oslo
- AALTO UNIVERSITY
- Alma Mater Studiorum - Universita' di Bologna
- Argonne
- CNRS
- Chalmers University of Technology
- Coast Community College District
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- George Mason University
- Georgetown University
- Imperial College London
- Institute of Biochemistry and Biophysics Polish Academy of Sciences
- Mohamed bin Zayed University of Artificial Intelligence
- Monash University
- NEW YORK UNIVERSITY ABU DHABI
- NIST
- Nantes Université
- Nanyang Technological University
- Northeastern University
- Purdue University
- Rutgers
- Rutgers University
- SciLifeLab
- The University of Iowa
- University of Amsterdam (UvA)
- University of California
- University of Canterbury
- University of Dayton
- University of Michigan
- University of Minnesota
- University of Nevada Las Vegas
- University of North Carolina at Charlotte
- University of Sheffield
- University of Southern California
- University of Stavanger
- University of Texas at Austin
- University of Tübingen
- Villanova University
- Virginia Community College
- 51 more »
- « less
-
Field
-
Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 24 days ago
well as to candidates with expertise in parallel and HPC computing combined with a solid understanding of combinatorial optimization. While prior HPC experience is an advantage for candidates from optimization and
-
Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 24 days ago
of leveraging task-based parallel and distributed programming techniques in the DDF-pipeline software components with the aim to accelerate such processing on high-performance heterogeneous computing platforms
-
computing IT or a scientific computing environment. Demonstrated expertise in administering one or more parallel file systems and supporting large-scale, multi-petabyte storage infrastructures. Experience
-
Applicants: Position is eligible for hybrid work subject to University policy . Job Summary: The High Performance Computing Data Storage Administrator II administers enterprise and high-performance computing
-
comprises research and teaching at bachelor's, master's and doctoral level in computer science, primarily in operating systems, compiler construction, systems programming, and parallel and distributed systems
-
integration, documentation, and collaborative development. Familiarity with parallelization and high-performance programming techniques such as MPI, OpenMP, multiprocessing, or distributed computing in Python
-
Computing Systems (PCS) group at the University of Amsterdam performs research on the design, programming and run-time management of parallel and distributed computer systems. The modeling, analysis and
-
members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience in sampling algorithms and related areas
-
administering distributed and parallel filesystems, managing project storage allocations, configuring quotas and permissions, and supporting metadata management. Performs backups, recovery operations, archive
-
against mission requirements. Architect high-performance storage solutions, parallel file systems, data movement capabilities, and storage hierarchies appropriate for large-scale computational workloads