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develop and compare ex vivo model systems derived directly from patient tumor tissue and blood. These models will be evaluated in parallel with an upcoming clinical trial at our department testing
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be controlled, measured, and related to the thermal and mechanical properties of the foams. Several formulations and systems will be studied in parallel to shed light on these three issues
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system for parallel imaging with acceleration, which permits faster temporal resolution for functional MRI scans. The scanner has industry-leading gradients for human MRI scanning (i.e., gradient rise time
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to analyzing data Knowledge of high-performance computing, such as parallelization, the use of C++, or interfacing with specialized linear algebra packages Other Information: Work arrangement: On-site Candidates
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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of the computing infrastructure that powers both data and computer intensive research. From high-performance computing clusters and parallel storage to data management and automation tools, you’ll help shape and
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scales through component-based parallelism. The focus of the post-doc position is to design and implement this pipeline -- developing native reasoning for rich combinatorial constraints, creating tools
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), parallelization (running loop iterations in parallel), enhancing data locality by fusion, and blocking (i.e. accessing arrays in a way that improves temporal and spatial data locality). A large number of
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complex dynamics. In parallel, collective decision-making mechanisms (e.g., opinion dynamics) will be leveraged at the high level to coordinate the desired behaviours of multi-agent systems in response
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific