78 professor-computer "https:" "https:" "https:" "https:" "University of Aberdeen" Postdoctoral positions at Aarhus University in Denmark
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friendly atmosphere of large and interacting communities for e.g. structural biology, molecular cell biology, computational biology, neurobiology, and molecular medicine that encourages lively, open, and
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, proteins and DNA origami constructs, and computational procedures for data analysis. The project is a collaboration between the single molecule biophysics and chemistry group at iNANO/Department
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interpretation in collaboration with interdisciplinary partners, including development and integration of open-source data pipelines You will report to Associate Professor Lotte Bonde Bertelsen. Your competences
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computing capacities as well as an extensive national and international researcher network. The department consists of nine research sections with around 350 highly skilled employees, of which approximately
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computational scientists. The position offers a unique opportunity to work at the interface of landscape ecology, biodiversity science, climate mitigation, and sustainable agriculture, contributing directly to
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Aarhus University with related departments. Contact information Before applying or for further information, please contact: Associate Professor Aurelien Dantan, +4523987386, dantan@phys.au.dk . Deadline
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advice, and education. We offer professional laboratories, greenhouses, semi-field, and field-scale research facilities, advanced computing capacities as well as an extensive national and international
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” funded by Independent Research Fund Denmark and led by Associate Professor Christoffer Basse Eriksen. The project aims to carry out the first large-scale study of the making of the Flora Danica (1761–1883
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laboratories, greenhouses, semi-field, and field-scale research facilities, advanced computing capacities as well as an extensive national and international researcher network. The department consists of nine
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substantial knowledge and research experience in areas such as computational fluid dynamics, turbulence modeling, data-driven methodologies, machine learning, and parallel computing. The candidate should also