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access to substantial computational resources (GPU nodes), advanced high-throughput instruments (including a FACS, mass photometer, ITC, SPR, and others), and state-of-the-art characterization tools
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management, high-performance computing systems, GPU acceleration, and parallel file systems * Documented experience with container and cloud technologies such as Docker, Helm, and Kubernetes * Ability
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Optimal Control Theory Strong programming skills in C++/Python/MATLAB Familiarity with parallelization and high performance computing (CPU and GPU friendly code) Experience with Machine Learning, generative
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frameworks (e.g., PyTorch). Engineering skills: GPU/cluster training, experiment tracking, data engineering. Ability to formulate research questions, run empirical studies at scale. *for students with
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dynamics, targeting large-scale systems equipped with GPUs and other accelerators. Key research topics include mixed-precision numerical methods, integrating machine learning into computational workflows
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even in modern GPU systems. This project investigates neuromorphic sensors and sensor fusion of multiple event-cameras in a real-time human-robot co-working space, where a robotic manipulator (a 7 DOF