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Field
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—or a strong affinity with—Bayesian Statistics, who is eager to contribute to our overarching research programme in high-dimensional statistics. As Associate Professor, you will play a leading role in
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to scientific audiences as well as to external partners, stakeholders, and other end users of applied ecosystem science Expertise building Bayesian networks for ecological application Expertise working with
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reinforcement learning (RL), active learning, Bayesian decision theory, and stochastic optimisation for partially observed and evolving systems. Key research directions include: adaptive data acquisition
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in mathematical modelling and Bayesian inference while learning from three collaborating chief investigators. You will also build your publication record and professional networks through seminars
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/modsim. Quantifying the activity of enzymes operating within the large-scale biochemical network is a fundamental challenge in Systems Bio(tech)nology. Here, the unknown parameters must be inferred from
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integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time
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such as Bayesian modelling and optimal control theory. Using state-of-the-art methods – including virtual reality, wearable sensing, motion platforms and advanced data analytics – you will place particular
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with academic and industry partners, alongside opportunities for research visits and collaboration in Scotland and elsewhere within a wider international network. The candidate will join a growing
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Qualifications Experience with graph neural networks, machine-learning interatomic potentials, or related scientific machine-learning methods for atomistic systems. Familiarity with uncertainty quantification
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. Mohseni Institute of Urologic Sciences (MIUS) providing access to cutting-edge facilities and collaborative research networks, and opportunities for leadership in translational science. Together, the UBC