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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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includes the opportunity for three weeks of training in higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity
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the research group, including on climate goals and advisory services in the dairy sector. Teaching students may be included in the work tasks, up to a maximum of 20% of the position. Your profile A PhD in
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will also have good opportunities to learn from and socialize with other postdoctoral fellows at the department. For more information about the department: https://www.slu.se/en/about-slu/organisation
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interdisciplinary research teams and internal and external partners. Required qualifications Applicants must have: A PhD in ecology, marine biology, statistics or a related discipline. Strong expertise in statistical
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research is conducted in co-operation with other universities/institutes and/or industry. Presently, our group consists of 1 Professor, 1 permanent researcher, 5 Postdocs and 8 PhD students. About the
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interdisciplinary research teams and internal and external partners. Required qualifications Applicants must have: A PhD in ecology, marine biology, statistics or a related discipline. Strong expertise in statistical
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your application: A doctoral degree in automatic control, electrical engineering, computational materials science or related. Research experience in battery tests, machine learning, data-driven
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machine-learning tools. Data analyzed include precursors such as volatile organic compounds, aerosol number and mass concentrations, chemistry, biological particles, cloud and ice condensation nuclei, light