77 fully-funded-phd-program-computer-science-eth Postdoctoral research jobs at Aarhus University
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, supported by advanced systems-level modelling and close collaboration with industrial and policy stakeholders. The successful candidate will contribute to the HyperCap research program focused on developing
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high-impact scientific journals. Your profile We are searching for a highly motivated candidate who has: A PhD in agronomy, engineering, biology, technical oriented sciences or similar Ability
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power. The project is funded by an ERC Starting Grant, the flagship funding program of the European Union, which supports frontier, cutting-edge research. Read more about the project here in an interview
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environment that supports this equilibrium. You can read more about family and work-life balance in Denmark . Aarhus University also offers a Junior Researcher Development Programme targeted at career
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, science/technology policy, innovation studies, management, education research, or a closely related discipline). Documented experience managing EU-funded projects for at least 3 years, including hands
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You have academic qualifications at PhD level within biomedical engineering, engineering, physics, medical physics, chemistry, biophysics or a related discipline. We expect applicants to have a strong
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science or similar. The Department of Chemistry at Aarhus University (www.chem.au.dk) is one of the leading European chemistry departments with a broad research program. It is undertaking a restructuring
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the Independent Research Fund Denmark, no more than 4 years have passed between obtaining the PhD degree and April 29, 2025 (taking into account any periods of leave). Applicants from various disciplines, e.g
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level, e.g. in medical physics, physics, biomedical engineering or computer science. It is mandatory that your PhD degree is on a topic relevant for this specific position, e.g. in medical image-based
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-year extension. The project is fully funded by the Independent Research Fund Denmark (DFF). The main objective of this project is to develop physics-constrained, data-driven turbulence models