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Science, Robotics, AI, or a related field Strong background in machine learning and robotics, with specialisation in one or more of the following areas: generative models, reinforcement learning, human-centred AI
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the University, with additional appointments in Mathematics, Engineering and Chemistry. Durham's strong commitment to this area of research is also demonstrated through its support for the EPSRC Centre
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Science, Robotics, AI, or a related field 2. Strong background in machine learning and robotics, with specialisation in one or more of the following areas: generative models, reinforcement learning, human
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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learning algorithms on graphs to model, characterize, predict, and design the thermal and physical behaviors of diverse material systems. Responsibilities also include the development of software codes
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of infrastructure and technology systems for mathematical/computational modeling and control theory for life-cycle management optimization and policy of smart and sustainable infrastructure and environment systems
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/GNC systems has traditionally relied on model-based techniques, which in turn, have their foundations in a solid body of mathematical proofs (such as guarantees of stability and robustness
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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Requisition Id 14907 Overview: The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is
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integrity in the design process calls for a technical model of the product concept, i.e., mathematical models of the product and its in-service environment, which inevitably must incorporate the influence