663 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" uni jobs in Germany
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cooperation partners in their research projects with state-of-the-art light and electron microscopes (https://www.leibniz-fmp.de/cellular-imaging ). We work with proteins, cell cultures, and model organisms
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fabrication. Receive individual trainings to learn state-of-the-art methodologies, comprising pulsed laser deposition (PLD), atomic force microscopy (AFM), advanced X-ray diffraction (XRD), electrochemcial
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settle into the team and are given structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome Days and Welcome Guide: https://go.fzj.de
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PostDoc/Senior Scientist - Process and Plant Design in the Field of Liquid Organic Hydrogen Carriers
) appointments FLEXIBILITY: Flexible working time models, including options close to full-time ( https://go.fzj.de/near-full-time ), allow you to tailor your working hours to suit your individual needs HEALTH
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this with expertise in high-performance computing and artificial intelligence using unique scientific infrastructures. Are you excited about working at the interface of natural and computer sciences? At
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and manufacturing technologies for the manufacture of innovative products. We develop new machines and processing strategies on behalf of customers, optimize existing production systems and implement
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learning new techniques The University of Regensburg aims to increase the proportion of women and therefore explicitly encourages qualified women to apply. The University of Regensburg is particularly
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, biochemical interactions and biological functions of small natural product molecules in and from plants and fungi ( https://www.ipb-halle.de/en/ ). Contact details: We are looking forward to receiving your
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and training provision within CAFE-BIO are available from the network website ( https://cafe-bio.org ) and the official EU page for the network ( https://cordis.europa.eu/project/id/101226762
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with