Sort by
Refine Your Search
-
Technician-HPC Posting Type Student Hours/week: Up to 20 hours p/week Eligibility: Work study preferred but open to all students Semester 2026 Summer Location Drosdick Hall Detailed Work Schedule Number
-
Technician-HPC Posting Type Student Hours/week: Up to 20 hours p/week Eligibility: Work study preferred but open to all students Semester 2026 Summer Location Drosdick Hall Detailed Work Schedule Number
-
la couche p. En distinguant l'annihilation séquentielle de l'annihilation simultanée et en propageant les incertitudes issues des interactions NN and NbarN, nous fournirons des entrées nucléaires
-
Technician-HPC Posting Type Student Hours/week: Up to 20 hours p/week Eligibility: Work study preferred but open to all students Semester 2025 Summer Location Detailed Work Schedule Number of positions: 1
-
Job Description Job Alerts Link Apply now Research Assistant (N.1 Institute of Health, A/P Christopher Asplund's Lab) University-Level Unit: Cancer Science Institute of Singapore Faculty/Department
-
machine learning libraries. Familiarity with collaborative coding environments (e.g., Git) and working on high-performance computing (HPC) clusters is an advantage. Good scientific writing and communication
-
. The project has access to the national computing infrustracture, TU/e HPC cluster SPIKE-1 , ASML HPC cluster, ASML datasets, and potentially custom data through collaboration with e.g. IMEC. Where to apply
-
training in high-performance computing and version control will be provided through the University of Sheffield HPC Centre, complemented by CDT and professional workshops on numerical geomechanics and
-
-on experience developing generative models Is highly proficient in PyTorch and/or JAX Has experience training large-scale neural networks on HPC or GPU clusters Has experience with representation learning and
-
-on experience developing generative models Is highly proficient in PyTorch and/or JAX Has experience training large-scale neural networks on HPC or GPU clusters Has experience with representation learning and