29 computing-optimization PhD positions at Technical University of Denmark in Denmark
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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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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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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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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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skills and a keen interest in data-driven research. Your role will be to apply the developed semantic infrastructure to concrete case studies—such as cross-unit scheduling, process optimization
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for the efficient formation of high-value compounds. Advanced NMR methods and computational data analysis will be compounded to devise novel reactions towards pharmaceutical precursors, polymer building blocks and
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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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Research Framework Programme? Horizon Europe - MSCA Reference Number DC6 Marie Curie Grant Agreement Number 101225914 Is the Job related to staff position within a Research Infrastructure? No Offer
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and kinetic modelling Expression, purification, and characterization of enzymes from fungal and bacterial sources Development and optimization of enzyme assays Structure–function studies of enzymes
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the optimization of bioactive compound extraction from various seaweeds for the development of fortified foods. This PhD position aims to (i ) identify suitable seaweed species for high-yield protein extraction, (ii