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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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project (Decarbonization of Heating and Cooling), we are seeking a motivated and qualified PhD candidate to design integrated district heating and cooling systems. Future thermal networks based on renewable
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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of the STAMP RSV Program, supported by the Stan Perron Charitable Foundation. The PhD candidate will play an important role in developing models of RSV transmission and vaccination efficacy to inform
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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PhD student(s) will join a vibrant team of postdocs, academics, and up to four PhD students working collaboratively across modelling, qualitative fieldwork, and optimisation techniques. PhD Research
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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applied research on the economics of public health, mainly vaccination and mathematical modelling. VAXINFECTIO, including CHERMID, is involved in several European Commission funded projects and is
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algorithmic aspects of cheminformatics. The position is founded by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases ”, led by