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Field
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-represented backgrounds. The objective of the research project is to perform Bayesian inversion to characterise the velocity field of 3D partial differential equations describing brain fluid and solute movement
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
between process parameters and material properties will be developed and subsequently exposed to Bayesian optimization to find the optimal set of parameters that improve process performance and material
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. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models for long-term forecasting. Collaborate closely with
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accessible measure of location. One option is to use skew versions of know distributions that leave the mode or median of the distribution at the origin. The main objective of this project is to explore, from
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uncertainty from climate projections into land-use forecasts. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models
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. Additional qualifications: It is advantageous to have experience in one or more of the following areas: Machine Learning & Bayesian optimization (Python, Supervised learning, Multi-objective optimization
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Areas (Codes 25–29) 1. Machine Learning (Code 25) Objectives: Support UFABC’s undergraduate and graduate programs, strengthen research in Machine Learning, and expand English-taught course offerings
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to have experience in one or more of the following areas: Machine Learning & Bayesian optimization (Python, Supervised learning, Multi-objective optimization) Additive manufacturing of metals Corrosion
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The objective of this postdoctoral position, in
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health. You will develop and apply cutting-edge machine-learning techniques to identify the most informative indicators of ecosystem change and use them to build dynamic Bayesian network (DBN) ecosystem