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Field
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the following key capabilities: A PhD in a relevant field Demonstrated experience working with ecological datasets Demonstrated experience in statistical inference and reporting Knowledge of models and theory in
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in computational surface science, electronic structure theory, computational materials discovery, or machine learning in materials science. Research competence and initiative proven through
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Postdoctoral Research Associate in Theory of Soft and Active Matter ( Job Number: 25000699) Department of Physics Grade 7: - £38,249 - £45,413 per annum Fixed Term - Full Time Contract Duration: 24
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case is central to this position. SimMobility is based on activity-based mobility modelling theory, simulating agent-level behavior such as route, departure-time, and mode choice within an activity-based
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activity patterns being associated with movements and others not. By using our novel techniques, that can drive precise patterns of activity distributed across many neurons, we can test different theories
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activity patterns being associated with movements and others not. By using our novel techniques, that can drive precise patterns of activity distributed across many neurons, we can test different theories
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. Exceptions from the 3-year limit can be made for longer periods resulting from parental leave, sick leave or military service. What you will do 1. Develop and implement group-theory-based codes to identify
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, Economics, Mathematics, or a closely related discipline. Strong background in computational social choice, algorithmic game theory, or AI safety. Excellent research track record with publications in relevant
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the theoretical and computational mechanics of shell structures, with a focus on extending these models to incorporate coupling with electromagnetic theory. This position is part of an interdisciplinary effort to
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. Qualifications PhD in Computer Science, Economics, Mathematics, or a closely related dis-cipline. Strong background in computational social choice, algorithmic game theory, or AI safety. Excellent research track