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++ coding skills • Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) • Enthusiasm and self-drive towards driving research forward :) How to Apply: • Required Documents: CV, research
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, with the option to extend. TUM’s benefits for employees (https://www.tum.de/en/about-tum/working-at-tum/services-for-employees/ ). Application If you are interested in joining us, please send us your
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our enthusiastic and collaborative group spirit. Post-doc: The applicant is expected to have a solid publication record in theoretical CS. Experience with biological applications, robotics applications
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the representation of women in science. Accordingly, we strongly encourage applications from qualified female candidates. How to apply Please send your application materials to office.nen@xcit.tum.de, with email
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Loriana Pelizzon via e-mail office_pelizzon(at)safe-frankfurt.de .
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interdisciplinary cooperations with partners and stakeholders from different domains. Candidates should have completed their Doctoral studies in Computer Science, Mathematics, Mechatronics, Electrical Engineering or
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strong publication history, including but not limited to conferences such as MICCAI, NeurIPS, ISBI, ICCV, ICML, ECCV, or others. Fluent familiarity with at least one coding language for ML or data analysis
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are looking forward to your application, including a letter of motivation describing your skills and research interest, your CV, and contact information for two references. Please send your application
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where they are underrepresented, therefore applications from women are explicitly encouraged. YOUR APPLICATION Please send your interest and full application as a PDF to patrick.bienert@tum.de or by snail
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the proportion of female candidates; applications from female candidates are therefore particularly encouraged. Contact Please send your application with a short letter of motivation conveying your interest and