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Your Job: This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining
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and BAT.jl projects. The position also offers opportunities to contribute to research in Bayesian inference and its application to physics in general. The DEMOS project aims to develop state-of-the-art
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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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: It is advantageous to have experience in one or more of the following areas: -Machine Learning & Bayesian optimization (Python, Supervised learning, Multi-objective optimization) -Additive
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Menopausal Women” with full-time employment for a duration of 3 years, starting in February 2026. Objective of the project: BrainAGE is a machine learning-based biomarker that estimates biological brain age
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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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development and statistical modelling in resilience assessment (e.g., dynamic/latent-variable models, Bayesian hierarchical models, causal inference, time-series analysis, cognitive modelling) Build robust
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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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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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”. The advertised position is in the context of the Bavarian government’s Master Plan for Nuclear Fusion dated February 11, 2025. The successful candidate is expected to promote the objectives of the Master Plan in