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, 2026, with the earliest start date 1 February, 2027. Further details and application instructions are available at: https://math.au.dk/en/about/vacancies/phd The webpage includes brief subject
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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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will consider techniques like flow matching, and use ideas from optimal transport and neural (stochastic) differential equations, invariant Kalman filtering and geometric numerical integration
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on facility location, storage, processing capacity, procurement, and inventory management. The project combines: stochastic and robust optimization, uncertainty modelling, large-scale supply chain design, and
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valued: nonlinear dynamics, condensed-matter physics, and stochastic processes. The ideal candidate is an experimentalist who enjoys not only setting up and performing complex experiments, but also
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of biophysics, non-equilibrium statistical physics, and cancer biology. Its objective is to understand how stochastic fluctuations and cell-cell interactions combine to drive the spontaneous emergence
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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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range of topics in numerical analysis and applied mathematics, including: Approximation Theory & Numerical Integration Mathematics for Data Science & AI Combinatorial Optimization Stochastics
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Stochastic Transport Operations Apply for this job See advertisement This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is
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inclusive, behaviour-aware, and financially sound, for business replication and policy making. Where to apply Website https://resurseumane.ase.ro/just-circle-measuring-and-advancing-circular-busine