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to contribute to a collaborative, interdisciplinary research environment Are eager to learn and explore new ideas at the intersection of ML and optimization Can program efficiently in one or more languages
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challenges. This PhD project aims to advance the efficient, controllable, and optimized use of renewable energy by integration of advanced TES technologies (latent heat and thermochemical storage) in
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latest predictive and generative AI for materials, we can offer you the best possible foundation. We seek two highly motivated and talented PhD students to join our group at DTU Compute, and we offer
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be applying methods such as sensitivity analysis, robust optimization, and stochastic modelling as you work on your project. You will be seconded with the Chalmers University of Technology (Sweden) and
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pharmacology. The PhD project will focus on testing and optimizing antisense oligonucleotides in preclinical in vitro models, as well as formulating these molecules into a novel biodegradable delivery system
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The primary tasks will be to: Synthesize thin films of solid-state battery components, following established protocols. Optimize the sensing schemes of a new state-of-the-art commercial scanning NV magnetometer