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biosynthetic pathways for microbially-derived molecules and understanding how microbial molecule production can be modulated for disease prevention and therapeutic benefit. Using a combination of computational
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, and train deep learning models on the resulting data to design new antibiotic compounds that evade both current and likely future resistance mechanisms. Your computational work will directly steer
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, catalysis and/or surface science. For Topic 4, candidates must have documented skills within computational modelling of atomistic processes. Experience in scientific programming, e.g. using Python, is
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1 Mar 2026 Job Information Organisation/Company Aalborg Universitet Department The Faculty of Engineering and Science, Department of Energy, Electric Power Systems and Microgrids Research Field
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components for the 3D-CIRCULAR educational and certification programmes in collaboration with partner institutions. Managing and documenting progress for the second and third programme cohorts. Facilitating
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-year period and is funded by a Carlsberg Foundation Accomplish Grant to Prof. Nanna B. Karlsson. About the position This position is part of the research programme REGLA, investigating the physical
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
Latin intellectual traditions. The project combines intellectual history with computational text analysis to examine large, historically complex corpora spanning multiple centuries and languages. The core
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to our research on communication behaviour in group conversations. Our work employs state-of-the-art technology and laboratory facilities, including a wide range of egocentric sensor systems
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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Two postdoctoral positions (3-year) in Experimental Evolution of Methanogenic Microbiomes in Bioe...
project at the interface of directed experimental evolution, microbial ecology, and bioelectrochemical engineering. The project combines laboratory evolution approaches with omics-based analysis