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entitled “Beyond Data-Augmentation: Advancing Bayesian Inference for Stochastic Disease Transmission Models”. The overarching aim of the project is to develop the next generation of statistical tools
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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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, hydrogen systems, maritime or port energy systems, data centre energy management, smart grids, stochastic optimization, deep learning, safe reinforcement learning, or quantum-inspired optimization. A strong
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programs (internships, fellowships, or full‑time roles). Familiarity with simulation‑based models (e.g., physics‑based, network‑based, agent‑based, or stochastic simulations) for analysis, experimentation
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, network‑based, agent‑based, or stochastic simulations for system analysis, experimentation, or decision support. Skills & Attributes Required Strong proficiency in Python and modern ML/AI development
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models, stochastic processes on networks and graphs, network communication processes, and reports. The fellow will work with the other SUPPORT fellows to develop statistical methods and data resources
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Position Description The Centro de Investigación en Matemáticas (CIMAT: https://www.cimat.mx/ ), located in Guanajuato, Mexico, invites applications from researchers in the field of Statistics for a
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optimization of PDE-based problems involving uncertainties or stochastic components. We are looking for an internationally recognized individual who is a leader in the field of Numerical Analysis of Partial
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; develop and validate an astrodynamics-based orbit determination algorithm using TFC, including hybrid solutions with stochastic filters (eg, EKF or UKF); integrate and calibrate optical sensors and develop
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Sensing and Communications for Future Vehicular Systems: A Network of Doctoral Students” (ISLANDS) – see https://www.islands-mscadoctoralnetwork.eu/ . Τhe chosen candidate will be hired by ACG-RC subject to