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Universiteit Amsterdam welcomes applications for a two-year Postdoctoral position in Reinforcement Learning for Stochastic Optimization. The candidate is expected to conduct high-quality research
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to extend the operational lifespan and reduce the overall weight of wind turbines. By innovating ways to lower mechanical loads on critical components and optimizing material usage, we aim to pave the way
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the operational lifespan and reduce the overall weight of wind turbines. By innovating ways to lower mechanical loads on critical components and optimizing material usage, we aim to pave the way for a truly
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on the results of the Erasmus+ project EDDIE. When it comes to the research part: This PostDoc project explores how artificial intelligence (AI) can be leveraged to optimize energy portfolios for local energy
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-based optimization) for NP formulation design, targeting specific therapeutic outcomes such as blood-brain barrier permeability and tumour accumulation. Couple generative models with counterfactual
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Bilevel programming (BP) is a powerful mathematical framework for modeling hierarchical decision-making processes involving two players: a leader and a follower. In energy network design, for example
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to a platform that supports researchers in understanding and analyzing complex respiratory time-series data. You will merge codebases, implement dedicated data containers, port and optimize signal
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that prepare professionals for future roles in a rapidly evolving energy sector. By working in an interdisciplinary team, you will contribute through enquiry-based approaches to shaping a responsive ecosystem
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of the urban soil/subsoil in Amsterdam required for optimal tree growth. Ecosystem services include: storing water in the unsaturated zone; draining water via groundwater; sequestering carbon; filtering and