57 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Postdoctoral research jobs at Nature Careers in Denmark
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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
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
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biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and epigenetic mechanisms
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning for improving
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polar orbit, passing near the poles about 15 times per day and regularly observing the CIFAR study region. Its payload - two optical cameras, a thermal camera, and onboard machine-learning capabilities
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these disciplines. Read more here: https://www.sdu.dk/en/om-sdu/institutter-centre/fysik_kemi_og_farmaci/ominstituttet Application deadline: 21 January 2026 at 23:59 hours local Danish time Please see the full call
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highly desired. Strong communication skills, the ability to collaborate effectively within the team, and proactive working style are essential. The candidate should be motivated, open to learning new
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University (http://bio.au.dk/en) and work in the Section for Microbiology at this department. The section employs 12 permanent scientific staff and ~20 PhD students and postdocs. Research at the section covers
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students. The department is responsible for two educations: Molecular Biology and Molecular Medicine with a yearly uptake of 160 students in total. Please refer to http://mbg.au.dk/ for further information
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learning, where PhDs and postdocs receive comprehensive insights in the cellular processes underlying gene expression, as well as a clear view of their medical importance and potential for a future research