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integrating agent-based approaches, bottom-up simulations, continuum models, and theory. This role offers a unique opportunity for a generalist to contribute to The Institute’s transformative vision
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employment. Please indicate the request in your application. Tasks: scientific research and development activities in the field of agent-based traffic modeling and simulation, e.g. on scenarios of sustainable
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well as high-throughput screening strategies to identify small molecular compounds that might serve as novel therapeutic agents in disease using cell culture, kidney organoid, and mouse models. Successful
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well as high-throughput screening strategies to identify small molecular compounds that might serve as novel therapeutic agents in disease using cell culture, kidney organoid, and mouse models. Successful
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eventually build a distributed (perhaps federated learning) learning/communication system within multiple robot agents, leveraging digital twin. Please fill out the google form (mandatory), which we can know
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. Consider a self-adaptive IoT network such as a smart home that autonomously manages energy consumption while balancing multiple, often conflicting requirements, such as comfort, cost efficiency, and
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University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations. Conduct
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, molecular dynamics simulations using ab initio and machine-learning potentials, and the development or application of machine-learning tools for feature extraction, property prediction, and inverse molecular
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dynamics simulations to investigate photoinduced processes and connect them to timescales obtained from nonlinear electronic spectroscopic measurements Plan and conduct simulations and work with
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that would give you an advantage) Experience in computational modelling (e.g., agent-based Bayesian models, cognitive learning models, machine learning, robotics). Experience in annotation software such as