199 associate-professor-computer-"https:"-"https:" Postdoctoral positions at Nature Careers
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Postdoc (f/m/d) on Generative AI for de Novo Protein Design / Completed university studies (PhD) ...
research Your profile # Completed university studies (PhD) in a relevant field, such as molecular biology, computational biology, bioinformatics, genetics, computer science, mathematics, or equivalent
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advanced programming skills in a high-level computer language (Python or related) hands-on experience with instrumentation development excellent oral and written English skills collaborative mindset Skills
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) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and
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) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and
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combining LLMs, molecular measurements, and multi-scale imaging. Your profile PhD in computer science, mathematics, physics, bio-/medical informatics or related fields, specializing in image analysis
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downstream chromatin locus enrichment (LacO/LacI capture) to enable molecular characterization of repressed loci. You will be involved in identifying proteins and histone modifications associated with
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natural and AI-designed protein domains, along with an engineered fusogenic protein. The technology has been recognized with the m4 Award, the GO-Bio next program, and is currently under revision in a top
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The Leibniz Institute on Aging – Fritz Lipmann Institute (FLI) in Jena is a federal and state government-funded research institute and member of the Leibniz Association (Leibniz-Gemeinschaft). FLI’s
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
for environmental challenges, are also encouraged to apply. The postdoctoral researcher will work within an interdisciplinary team of computational and applied scientists. The work will be done in close collaboration
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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