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division at the department of Electrical engineering at Chalmers. Here, a team of PhD students, post-docs and senior researchers are working on modeling and numerical optimization of problems in the areas
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experience in microstructural analyses. Familiarity with mechanical testing procedures and, ideally, experience in numerical simulation (e.g., finite element methods). Strong analytical skills, an independent
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preferably has strong programming skills and experience with the modeling and simulations of fluid or solid mechanics or ice sheet flow and deformation (for example by use of finite element/volume methods
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Project advert Perfluoroalkyl substances (PFAS) are manmade chemicals that are ubiquitous within society. PFAS offer water/oil repellence and non-stick properties, featured in numerous consumer
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numerical methods for quantum systems is preferred. Experience with neural quantum states is a bonus. Good programming skills in Python. Familiarity with JAX is a bonus. Proficient in spoken and written
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of data-driven approaches within these multi-parameter models to produce faster and more robust correlations and tools that can be incorporated within industrial methods and have an impact on future designs
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and very good knowledge in quantitative and qualitative research methods Good knowledge of statistical software (e.g. SPSS or STATA or R or JASP) Strong commitment and the ability to work in a team
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will lead to natural collaboration opportunities. The primary methods used in this project will be experimental, involving fluid characterisation and high-speed imaging experiments, using Phantom high
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a strong specialization in Sound and Vibration (We also welcome applications from candidates who will graduate soon). Solid knowledge of structural mechanics and numerical methods Proficiency in
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spanning a broad range of research areas - including methods for high-dimensional data and data integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and