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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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In manufacturing, a wide variety of use cases exist where Deep Learning (DL) and Machine Learning (ML) are successfully applied. Examples of use cases include the production of rockets, stem cells
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applications for the position of Professor (W3) for effective teaching and learning in subject didactics (f/m/d) to commence as soon as possible. The professorship is intended to advance internationally visible
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) car and bicycle parking spaces Be part of change You will research the current state of the art. You will implement, train, and test deep learning model architectures. You will develop approaches
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University Medical Center of the Johannes Gutenberg University Mainz | Mainz, Rheinland Pfalz | Germany | 3 months ago
), is offering a fully funded PhD position in the area of statistical learning, machine learning, and survival analysis applied to large-scale proteomics and multi-omics cohort data. The PhD project
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learning for decentralized AI model training for tool wear detection and measurement in milling processes within the »FL4AI« project. A custom dataset has been acquired, consisting of microscopic tool wear
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/m/d) in Machine Learning Applications to Sustainable Energy Management. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like
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18.03.2026 Application deadline : 30.04.2026 The Cluster of Excellence “Machine Learning – New Perspectives for Science” at the University of Tübingen is seeking a Scientific Director (m/w/d, E14 TV
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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macromolecular dynamics with machine learning, statistical mechanics, molecular simulations, and experimental data. The joint project “FAIME – Flexible and Efficient AI-driven Molecular Simulation Engine” is part