52 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" uni jobs at Forschungszentrum Jülich in Germany
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, 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 tasks: You will work together
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environment, we offer you much more: https://go.fzj.de/benefits We welcome applications from people of diverse backgrounds, in terms of age, gender, disability, sexual orientation/identity as
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experience in scientific computing and software development; familiarity with C++ and Linux environments is an advantage Strong background in deep learning for image analysis / computer vision, ideally
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mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time-lapse data Proven programming expertise in
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projects SCIENTIFIC ENVIRONMENT: You can expect excellent scientific equipment, modern technologies, and qualified support from experienced colleagues. On top, you will receive individual training to learn
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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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physical research. Forschungszentrum Jülich has recently become part of the German Instruct-ERIC Center offering external cryo-EM user access at the European level. Your tasks in detail: Organize and oversee
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. Usadel, specializes in data integration, classical bioinformatics, data science, and machine learning. The offered position will focus on the ELN-RO project, which has the aim to establish seamless
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! This job offer is closely linked to a related opening at IET-3 at Forschungszentrum Jülich within the same project consortium: https://www.fz-juelich.de/en/careers/jobs/2025-362 Please feel free to apply
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institute Supervision from both chemical engineering and machine learning experts, ensuring strong interdisciplinary guidance Your Profile: Current Master`s student in Process Systems Engineering