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of full-time. Your qualifications You have graduated at the Master’s level in Molecular Biology, Computational Biology, Immunology, or a related field, or completed courses with a minimum of 240 credits
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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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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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failures. We offer access to unique experimental data and computational tools developed by our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel
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. These positions involve advanced numerical simulations and analysis of spacecraft data. The positions are full-time, 100% funded for four years and lead to a doctoral degree in Computational Physics. The expected
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build the sustainable companies and societies of the future. The EISLAB division of the Department of Computer Science, Electrical and Space Engineering conducts research within Cyber-Physical Systems
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) programme and research school Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures
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social issues that require more knowledge. In order to both sustainably use and safeguard forest biodiversity, a coherent basic science research program is needed that addresses large and complex issues
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the role of forests in climate change are now key social issues that require more knowledge. In order to both sustainably use and safeguard forest biodiversity, a coherent basic science research program