265 computational-physics "https:" "https:" "https:" "https:" "NORTHUMBRIA UNIVERSITY" Postdoctoral positions at Nature Careers
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Sustainable travel to work: subsidized Germany job ticket Our Corporate Health Management Program offers a holistic approach to your well-being Develop your full potential: access to the DKFZ International
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? Then the Department of Electrical and Computer Engineering invites you to apply for a 2 year postdoc position bridging research with industrial implementation and innovation. Expected start date and
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, proteins and DNA origami constructs, and computational procedures for data analysis. The project is a collaboration between the single molecule biophysics and chemistry group at iNANO/Department
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friendly atmosphere of large and interacting communities for e.g. structural biology, molecular cell biology, computational biology, neurobiology, and molecular medicine that encourages lively, open, and
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computational scientists. The position offers a unique opportunity to work at the interface of landscape ecology, biodiversity science, climate mitigation, and sustainable agriculture, contributing directly to
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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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) 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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Work group: Institute of Materials Physics Area of research: Scientific / postdoctoral posts Starting date: 23.12.2025 Job description: PostDoc at the P05 Nano-Tomography Endstation Job ID: 940
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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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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
decomposed into modular sub-components that can be either process-based models and/or deep learning models. MCL has the flexibility to replace any uncertain process description with a deep learning model