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, based on simulation models in Aspen, COMSOL, etc. c. Control theory & applications — including nonlinear systems, MPC, reinforcement learning, stability analysis, etc.
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the Department of Stem Cell and Regenerative Biology at Harvard University, is working to identify the mechanisms controlling mammalian brain development and to define cellular and molecular pathways disrupted in
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experience in one or more of the following areas: hybrid systems and/or discrete event systems; systems and control; reachability analysis and/or set-based methods; formal methods; optimisation and
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Strong command of behavior cloning, reinforcement learning, or related learning-based manipulation methods Proficiency in Python and modern deep learning frameworks (e.g., PyTorch) Proven ability
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of Melbourne, has two closely connected aims. First, we will develop a formally verified reference monitor on top of seL4 for the secure containment of AI agents, including mechanisms for dynamically controlling
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for cold regions hydrology in Canada and is known around the world for advances in snow, glacier and frozen ground hydrology and modelling www.usask.ca/hydrology . The work will be based out of its
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reference monitor on top of seL4 for the secure containment of AI agents. We will develop new mechanisms for dynamically controlling agents’ capabilities and information flows, together with machine-checked
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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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, generating process, material, and structural data to support model development, validation, and process consolidation. Develop and apply physics-based and data-driven modeling frameworks to describe, predict
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written communication skills in English. Desirable qualifications Experience with spheroids, organoids or tissue-engineered models. Experience with web-based software application to analyze, integrate, and