156 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Forschungszentrum Jülich
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JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de/en/judocs Targeted services for international employees, e.g. through our International Advisory Service In
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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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structured continuing education ( https://www.fz-juelich.de/en/judocs ) Targeted services for international employees, e.g. through our International Advisory Service The position is for a fixed term of 3,5
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Independent way of working Basic programming skills (Python) advantageous Very good knowledge of German or English (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), ideally
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months In addition to exciting tasks and a collegial working environment, we offer you much more: https://go.fzj.de/benefits We welcome applications from people with diverse backgrounds, e.g. in terms
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. Willingness to learn various electrochemical methods. High degree of independence, motivation and reliability. Our Offer: We work on the very latest issues that impact our society and are offering you the
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for doctoral students (HITEC): https://www.hitec-graduate-school.de/home FAIR REMUNERATION: Depending on your qualifications and assigned responsibilities, you will be classified according to pay group 13 (75
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specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs VACATION: You will receive 30 days of vacation SUCCESSFUL
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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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Your Job: In this position, you will be an active member of the SDL “Fluids & Solids Engineering” and will collaborate strongly with the SDL “Applied Machine Learning”. You will have the following