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project on neuromorphic imaging for space applications. We are looking for an enthusiastic researcher (post-doctoral researcher) who wishes to design and implement a rad-hard neuromorphic CMOS image sensor
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training pipelines using modern ML frameworks Generating data on miBd–pMHC interactions to guide iterative model optimization, espeicially for specificity Benchmarking AI-designed recognition modules against
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dynamics information. As a postdoc, you will contribute to the development of single molecule fluorescence real-time imaging methodologies using both experimental approaches, involving model nucleic acids
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validation in rodent migraine models Close collaboration with computational protein engineers and clinical researchers Data analysis, manuscript preparation, and supervision of students where relevant
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, organoid-based models and in vivo cancer and infection models Integration and analysis of transcriptomics and proteomics datasets Establishment and maintenance of standardised experimental pipelines Data
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generation Developing and optimizing generative models for de novo minibinder design Integrating structural biology data into AI pipelines for receptor–ligand interaction modeling Fine-tuning large protein
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to deploy and scale, by running plug-and-play analytics inside modern drives or on a plant controller using only electrical signals already measured by the drive, while minimizing data export and supporting
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quantum networks, where one bit of information is encoded in the quantum state of a single photon. You will be part of a team of 10-12 people between senior staff, PostDocs and PhD/Master students
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2026 or soon thereafter. Information on the department can be found at: BRIC – University of Copenhagen (ku.dk) Our research The aim of our group is to decipher how differentiation pathways
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aspiring scientists with polished skills to expand the field of molecular thermodynamics for aqueous electrolyte systems. This post-doctoral project is part of the ERC Consolidator Grant “Revolutionizing