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of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. We seek to appoint a postdoctoral Research Fellow (fixed term, 30 months) to work on uncertainty quantification in
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advances the mathematical foundations, algorithms, and real-world applications of epistemic uncertainty in machine learning, with a strong focus on imprecise probabilities, uncertainty representation and
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 12 days ago
). Develop an accompanying uncertainty‑quantification (UQ) layer on top of EM to produce calibrated credible/prediction intervals. Train, validate, and stress‑test on ECoG data, benchmarking against
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research partners Proficiency in DAMASK, AMITEX, Abaqus & MOOSE Experience with MTEX & DREAM3D (advantageous) Application of machine learning (e.g. Gaussian Process) for surrogate modelling & uncertainty
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agents, including uncertainty quantification at the agent’s level. The project will bring together ideas from Statistics, Probability, Statistical Machine Learning, Statistics and Game Theory and is an
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planning algorithms for GPS-denied lunar environments and extreme operational conditions stochastic optimisation frameworks for mission-critical decision-making under uncertainty Research areas and technical
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experience in data-knowledge fusion-driven dynamic modeling of complex structures, specializing in uncertainty quantification of nonlinear systems and intelligent model order reduction methods, with at least
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within the Environmental Informatics Hub and reporting to the Director, you’ll help lead research into sequential decision-making under uncertainty, such as reinforcement learning and adaptive management
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of foundation codes. Handling spatio-temporal statistics of forecast uncertainty will be a key consideration. This kind of downscaling with machine-learning methods is a rapidly advancing field and it is an
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of clinical trial outcomes (e.g. doi: 10.1038/s41467-024-53065-z). Given the uncertainty associated with intervention outcomes, we also aim to explore adaptive trial designs to enable studies to start small and