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decision is made Strong background in computational modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux
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to develop complement/augment classical CFD methods with quantum algorithms/techniques. The work lies at the intersection of multiphase flow physics, numerical modeling, and quantum computing. Who we
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implementing numerical models, calibrating them with real measurement data, conducting sensitivity and scalability analyses, and comparing energy community investments with conventional grid reinforcement
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development related to the above areas. Publications in first class journals and highly competitive conferences in areas relevant to the work, i.e. network modelling and protocol emulation in virtualised
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causal inference with structural economic modelling. Subject area The subject area for this position is economics. Fields of specialization: Labour Economics – AI and the Economy; Econometrics – Structural
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research on the effects of artificial intelligence (AI) on productivity and labour markets, combining micro-level causal inference with structural economic modelling. Subject area The subject area for
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proficiency in English. Documented experience in CFD and numerical modeling, preferably with OpenFOAM, Nek5000, or LBM. Strong programming skills (C++, Python, or similar). Ability to work independently and
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in AI and cybersecurity to develop novel solutions to cyber-resilient AI for the benefit of Swedish industry and society. The vision is to make Sweden a role model in secure trustworthy AI by
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experimental, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase flow systems and reactors Quantify model uncertainty
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algorithms/techniques. The work lies at the intersection of multiphase flow physics, numerical modeling, and quantum computing. Who we are looking for The following requirements are mandatory: A doctoral