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for scientific purposes. The postdoc will work with Prof. Daniel Metcalfe (Umeå University, Sweden) and Dr. David Bartholomew (Botanic Gardens Conservation International, Brazil), and collaborators within
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outside of Sweden, for example a 4-year bachelor's degree is accepted. Strong knowledge of hydrodynamics, CFD, turbulence modelling, and structural mechanics. Understanding of the numerical methods behind
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, within the Centre for Image Analysis at the Department of IT and conducted alongside researchers developing computational methods with a particular focus on deep learning and image analysis. The project
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the Data-Driven Life Sciences initiative – one of Sweden’s largest and most ambitious research initiatives, focusing on using data, computational methods, and artificial intelligence to study biological
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triboelectric nanogenerators and thermoelectric systems, tailored to a range of temperature environments. In parallel, research also focuses on the design of earth-abundant catalysts to drive green hydrogen
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of the numerical methods behind CFD and turbulence models. Experience in analyzing CFD data and interpreting simulation results. Excellent command of written and spoken English. Experience writing scientific reports
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and
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complete. Incomplete applications and applications sent by email will not be considered. Application deadline: 11 May, 2025 For questions please contact: Prof. Leif Eriksson, Geoscience and Remote Sensing
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environment at bachelor's and master's level within the Architecture Program. The teaching will to a large extent involve individual supervision and coaching of students where the design process and methods
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advanced spectroscopy and electrochemical methods. Strong proficiency in written and spoken English. Demonstrated early career achievements, including scientific publications. Contract terms Full-time