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discount programs Posting Summary The Laboratory for Biomolecular Simulation Research (http://lbsr.rutgers.edu ) and Institute for Quantitative Biomedicine (https://iqb.rutgers.edu/ ) at Rutgers, the State
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documentation practices. Experience with GPU-accelerated hardware platforms and software engineering including NVIDIA GPUs and CuPy/CUDA/C++ programming. Familiarity with 5G/6G wireless standards and AI/ML
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Python, ML, and AI for chemical applications Preferred: Familiarity with HPC systems Proven track record of research in ML/AI for chemistry Strong coding foundation (Python) Knowledge of C++ and CUDA
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information can be found at https://www.humboldt.edu/hr/employee-benefits . Please note that this is an internal recruitment open only to active, stateside, Cal Poly Humboldt Employees. Position Summary
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of Duties. Where to apply Website https://form.erecruiter.pl/form/65999ecbe10948a39cfb7af9bbeb4701?skkcfg=0596d66… Requirements Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications
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with staff ID card For more details, please see: https://hr.utexas.edu/prospective/benefits and https://hr.utexas.edu/current/services/my-total-rewards Must be authorized to work in the United States
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 3 months ago
and GPU computing infrastructure (CUDA, etc.); Solid understanding of IT security principles (ISO 27001, NIS2) and data protection laws (DSGVO, DSG) as applied to both enterprise and research data
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Posting Number R260058 Posting Link https://www.ubjobs.buffalo.edu/postings/61964 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89 Posting
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configuration, and performance tuning) and NVIDIA GPUs/accelerators with associated drivers and libraries (CUDA, NCCL) in clustered environments. Linux at Scale and Cluster Provisioning: Proficiency managing
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at the Technical University of Munich (TUM) invites applications for one PhD position. The student will work on developing scalable distributed preconditioners in Ginkgo (https://github.com/ginkgo-project/ginkgo