647 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" uni jobs in Germany
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | about 1 month ago
programming, machine learning (scikit-learn, PyTorch/TensorFlow), ontologies (OWL/RDF), and/or computational cognitive modelling Interest in interdisciplinary research at the interface of computer science
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start? Have a first look of what it’s like working at ICE-2: https://go.fzj.de/ice-2 We are offering an interesting PhD Position – Techno-economic assessment of geothermal plants with material co
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methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team orientation excellent
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investigations as well as analyzing and interpreting the results of these investigations developing and testing innovative spinning technologies and modifying existing machine technology preparation of scientific
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ScienceCountryGermanyCityRostockPostal Code18059StreetAlbert-Einstein-Straße 22Geofield Contact City Rostock Website https://www.uni-rostock.de/en/ Postal Code 18051 E-Mail alke.martens@uni-rostock.de STATUS: EXPIRED X (formerly Twitter
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platform - a tool designed to help scientists organize and promote scientific events. More details and application instructions: https://www.lifescience.net/jobs/162770/internship-for-the-science-even… Where
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submitted online via the appointment portal of Heinrich Heine University Düsseldorf: https://berufungsportal.hhu.de If you have any questions regarding the position, in particular concerning the bioeconomy
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, the faculty of Humanities and the Leibniz University, in particular at the Center for Atlantic and Global Studies (CEAGS) within the framework of the faculty's research focus “Atlantic World” Ability to teach
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to further reflect experience. Please follow this attached link for more details https://www.eso.org/public/jobs/conditions/intstaff/salary-structure/ . ESO aims to support members of personnel in maintaining
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Design and use of data spaces and digital twins for materials and autonomous material laboratories Use of deep learning methods to connect theory, simulation, and experiments Integration of high throughput