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the design questions using a computational approach to simulate the performance of thermoelectric generators, and subsequently use the model to dimension and design the thermoelectric elements for the heat
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At the Faculty of Engineering and Science, AAU Energy, a position as Postdoc in AI-augmented process control, is open for appointment from 01 July 2026 or soon hereafter. The duration of the position is two years. Your work tasks The main task of this postdoc position will dedicate on research...
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University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here . At the Faculty of Natural Science at Aarhus University, we
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structures. You will work closely with computational researchers to gather data, evaluate AI predictions, and design experiments. You will work in a team with 7 PhD-students and 4 postdoctoral researchers and
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systems and a vibrant interdisciplinary community at Aarhus University, including collaborators in biophysics, neurodegeneration, spectroscopy, and computational modeling. You would join a dynamic research
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The project will involve both experimental and computational work and the candidate is expected to be comfortable with both. The candidate is expected to have (or be close to finishing) a Ph.D. in molecular
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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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, 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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entering and working in Denmark here . Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will