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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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of adaptive methods for time-dependent partial differential equations (PDEs). The position is funded by the Dutch Research Council (NWO) via the Vidi research project Optimal adaptive spacetime boundary and
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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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://www.universiteitleiden.nl/en/staffmembers/laura-heitman#tab-1 at Leiden University! What you will do Project objectives are: Develop expression and purification methodologies for GPCRs Develop and optimize affinity selection
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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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. In this project, we aim to prove the concept of hard/soft concrete composites. The research will include: Computational modelling and optimization of concrete architectures Experimental testing and
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the Commencing CRISPR Commons project, funded by the Gates Foundation, which aims to establish a plant‑optimized, freedom‑to‑operate genome editing platform based on the ThermoCas9 nuclease. CRISPR/Cas systems