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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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nanophotonic sensors that disentangle multiple physical parameters from complex optical spectra. This approach raises fundamental questions on how information about parameters is optimally encoded and retrieved
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neuroscience. has expertise in molecular and cellular biology. has hands-on experience with advanced (super-resolution) microscopy. is enthusiastic to optimize labeling strategies and quantitative analysis
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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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capabilities, existing technology can only handle relatively small-scale problems. Information In the SymBi project (Exploiting Symmetries for Faster Bilevel Optimization Algorithms), we address this limitation
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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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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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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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that strengthens collaboration, reduces time-to-job, and drives innovation for a climate-neutral society. In this position, you will design and optimize learning communities that integrate learning