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datasets in scalable GPU-based computing environments. What we provide: A competitive compensation package, with comprehensive health and welfare benefits. A supportive team environment that promotes
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approaches, the application of meta learning, and the integration of convex optimization layers Increase inference efficiency (e.g., GPU acceleration) and assess the applicability domain of learned algorithms
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modules, and monitor training progress. Display performance metrics (e.g., inference time, GPU utilization, throughput, ROI impact) in real time. System Integration Work with the research team to connect AI
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wide range of academic fields, Ghent University is a logical choice for its staff and students. Image Processing and Interpretation (IPI, http://ipi.ugent.be ) is an imec research group at Ghent
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 1 month ago
collaborators # Ability to set individual goals, self-structure and fulfill milestones # Parallel programming, ideally in C++ and with GPUs # Knowledge with Python # Excellent command of English (spoken and
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obtained. The simulation activities must be conducted using high-performance scientific computing systems, with particular reference to the use of advanced architectures and GPU accelerators, in order to
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(€39,005.40 gross/year, 30 hours/week) Access to a modern GPU cluster Conference travel and active support towards publications How to apply Email us with your CV, a GitHub repo or code sample, and a short
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at the IRIT-ENSEEIHT campus in Toulouse. Integrated within the REVA team at IRIT. Strong interaction with ALICIA-Vision LabCom partners (CNRS / Technicolor-Mikros). Where to apply Website https://emploi.cnrs.fr
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with excellent facilities for protein science research. There will be direct access to advanced biophysical infrastructure in the biophysics core facility headed by the PI, a GPU cluster with working
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learning, multicore and GPU programming, and highly parallel systems. Good knowledge in one or more of the following programming languages/environments: C/C++, Python, PyTorch (or similar), and Cuda. Place