156 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Forschungszentrum Jülich
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Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the
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Infrastructure? No Offer Description Work group: IAS-8 - Datenanalyik und Maschinenlernen Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student in machine learning to work within
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, motivation to learn new skills to expand scientific knowledge Excellent communication skills and ability to work in an interdisciplinary team Very good written and oral communication skills in English (at
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Your Job: At the Institute for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) we are looking for a PhD student in machine learning to work within a project linked to the
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strong Excel skills You are organized, reliable, and proactive You are a good communicator and enjoy teamwork You are comfortable working in English (at least B2 level according to the CEFR: https
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laboratories Based on the complexity of the project, motivation to learn new skills to expand scientific knowledge High degree of analytical working style Excellent communication skills and ability to work in an
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the following areas desirable but not essential: electrocatalysis, rheology, coating technology, machine learning Intrinsic motivation to show initiative, creativity, and to work independently Excellent
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English (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), ideally supported by a certificate confirming the language level. Knowledge of German is not prerequisite
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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the INW-1 machine learning team on data handling, online analysis, design of experiments (DoE), and data categorization to enable efficient and automated evaluation of operando experiments Collaboration