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Field
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-learning–based segmentation, species classification and lineage tracking workflows for multi-species time-lapse data Optimise models and pipelines for real-time performance, enabling adaptive imaging and
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triggered by colloids, as well as methods for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate
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, machine learning, energy technology or related subjects Prior experience in building predictive models using regression techniques, neural networks (CNN, GNN) or symbolic regression Experience in
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, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently and collaboratively Effective communication skills and an interest in contributing to a
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Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and
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of Mathematics and Natural Sciences at Heinrich Heine University Düsseldorf is inviting applications for the position of a Professorship for Machine Learning (open rank: W2 or W1 with tenure track to W2
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the collected data in accordance with FAIR standards for collaborative use within the Decode project and for machine learning applications Presentation of results in team meetings and preparation of a
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Programme? Not funded by a EU programme Reference Number Bu- CIW 06 Is the Job related to staff position within a Research Infrastructure? No Offer Description WHAT TO EXPECT You will teach mathematics in
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knowledge with statistics, machine learning, Deep Learning and AI are an advantage • Good knowledge of the English language LanguagesENGLISH Research FieldEnvironmental science » Ecology Additional
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or Python) • Good knowledge of the English language • Experience with statistics, machine learning, Deep Learning and AI are an advantage • Familiarity with fundamental ecological concepts and experience in