80 optimization-nonlinear-functions-"Prof" Postdoctoral positions at Technical University of Denmark
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Job Description Are you passionate about leveraging IoT, machine learning, and optimization to make energy districts and communities more sustainable? We are looking for a highly motivated and
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platforms. Experience in high-performance computing or working with large-scale simulation environments. Prior work involving model calibration, optimization under uncertainty, or scenario analysis
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Location: South Kensington campus About the role: Applications are invited for a fully funded fixed-term position at the Research Assistant/Associate (PostDoc) level in simulating stratospheric
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reaction evolution mechanisms for magnesium-based binders, leveraging state-of-the-art experimentation and numerical modelling tools. This position is part of the prestigious Villum Synergy project
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functions in a non-invasive way through sensing the tiny magnetic fields produced by neuronal currents. Today, this need is primarily met by quantum sensors that must be operated at cryogenic temperatures
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genomic data from extinct and extant species, and machine learning, you will help develop a foundational tool for predicting extinction risk and advancing the use of genomics in conservation science. Job
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. The funding body is the Novo Nordisk Foundation. In parallel with research, you have the opportunity to take part in innovation activities with Copenhagen Microsystems , and this could be up to 20% of your time
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researchers to join our research activities focused on SOEC cell and stack components. Electrolysis and green hydrogen play a central role in Power-to-X schemes to produce green fuels and facilitate
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About Us King’s College London is one of the top research universities in the UK, with a strong tradition of interdisciplinary biomedical research. This role sits within a leading research group
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of single indistinguishable photons for photonic quantum information technology. Single-photon sources play an important role in photonic quantum information applications, which generally require near-unity