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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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-chemical-physics/ ) led by Prof. Alexandre Tkachenko at the Department of Physics and Material Science, we are looking for a PhD candidate to perform molecular dynamics simulations of different genetic
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modelling of materials and machine learning. Experience in atomistic modelling (molecular dynamics, density functional theory) and machine learning is important, as well as a strong interest in pursuing
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, your application should include (PDF format): A letter of motivation (max. 1 page) A detailed curriculum vitae. Please include an overview of your experience with molecular dynamics, density-functional
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on biological processes as well as the impact of biological processes on materials. Our ambition is to foster a dynamic teaching and research environment that is internationally recognized for its excellence in
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biological physicists who ask how physical mechanisms shape functional biological patterns. We combine statistical physics, nonlinear dynamics, mathematical modeling and data-driven simulation with physics
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time-scales: ab initio methods for the description of reaction processes, for the determination of electrochemical stabilities and for the optimisation of force fields; molecular dynamics simulations
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university graduates who wish to work towards a PhD in the fields of Biological Sciences (molecular cell and developmental biology, regenerative and degenerative biology, genetics, biochemistry), Biomedicine
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-driven simulation with physics-inspired data and image analysis, often in close collaboration with experimental partners, to identify physical principles behind biological dynamics and self-organization
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sensing, to improve worker/operator safety. This project will focus on using density functional theory calculations and ab initio molecular dynamics simulations. The project is a collaboration with Dr