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to complete the programme. Additional requirements: Very good oral and written proficiency in English. Very good knowledge in materials science or chemistry relevant for the position, for example chemistry of
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; significant practical experience in 3D image analysis or computer vision; knowledge and experience in scientific programming (python (preferred), Matlab or other relevant language) with application to image
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strong publication record in relevant fields Proficiency in programming (e.g., R, Python, Bash) Effective communication in English is required for daily work. After the qualification requirements, great
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science The holder of the position must be able to communicate in English Meriting: Skills in programming in Python Knowledge about life cycle assessment or future scenarios Knowledge about the Swedish
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empirical research, Software Development in programming languages and tools, Artificial Intelligence, Robotics, Natural Language Processing, Embedded Systems and Theoretical Computer Science. Subject
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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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will have access to a range of tailored resources and support, including programs & opportunities for mentoring, professional development, leadership training, and networking, as well as access
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Epidemiology Center (SEEC) at SLU within the Division of Microbial Ecology of the Department of Aquatic Sciences and Assessment. SEEC is part of SciLifeLab’s Pandemic Laboratory Preparedness (PLP) program, which
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of artificial intelligence, aesthetics, history of philosophy, epistemology, philosophy of mind, metaethics, metaphysics, normative ethics, political philosophy, philosophy of language, applied ethics, and
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, or relevant fields. Excellent programming skills in modern programming languages are required, as well as experience in computational or mathematical modelling. Experience with the analysis of biological data