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applications for the position of Research Assistant. Key Responsibilities: Study and analyze dataflow patterns in emerging data-intensive applications. Design and develop parallel file systems for node-local
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to computational problems Ability to code in a programming language to solve computational problems Awareness of computational infrastructure and its upkeep Ability to work on multiple projects in parallel and set
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programming language to solve computational problems Awareness of computational infrastructure and its upkeep Ability to work on multiple projects in parallel and set priorities Willingness to provide training
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solve computational problems Awareness of computational infrastructure and its upkeep Ability to work on multiple projects in parallel and set priorities Willingness to provide training to staff and
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. Programming & Software Development: Proficiency in Python, PyTorch, JAX, or other ML frameworks Computing: Some experience with large-scale datasets, parallel computing, and GPUs/TPUs. Algorithm Development
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parallel projects. Integrity and discretion when handling confidential information. Proficient in basic photography, Microsoft Office and Excel, Adobe Premium Pro, InDesign, Illustrator and Content
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/C++, and Python. Working knowledge for parallel programming models (MPI, OpenMP, CUDA, SYCL) Proven track record in GPU driver development, performance profiling, and debugging. Familiarity with Linux
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model is employed to forecast renewable energy availability, providing crucial insights for the design optimization process. The ML-assisted operation tackles the dynamic optimization of parallel energy