684 computer-programmer-"https:"-"Prof"-"https:"-"https:"-"https:"-"https:"-"CNRS"-"UNIV" positions in Germany
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Max Planck Institute of Animal Behavior, Radolfzell / Konstanz | Konstanz, Baden W rttemberg | Germany | 2 months ago
through a startup spinoff project funded by Max Planck Innovation’s MAX!mize program. Our platform makes behavioral analysis tools accessible for research and industry applications. Your tasks Coordinate
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the course of your doctoral program Our requirements Solid basic knowledge of cell culture as well as isolation of human primary cells Interest and experience in working with bioreactors, especially organ-on-a
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Flexible working hours Possibility of part-time work Family-friendly working environment Sustainable travel to work: subsidized Germany job ticket Comprehensive further training program, options
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evaluate the measurement results. You support the preparation and editing of project reports and presentations. What you contribute You are enrolled in a natural or engineering science degree programme, or a
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contribute PhD or master's degree in computer science or a related field with above-average grades Extensive knowledge, keen interest, and ideally practical experience in the field of cybersecurity or data
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the development of novel optical technologies addressing significant biological and medical challenges. The Mission: The successful candidate will play a key role in an ambitious research program focused
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research program focused on developing next‑generation multimodal imaging systems spanning the mesoscopic to microscopic scale. As part of a major research project and supported by extensive national and
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results, and discuss them in regular group meetings. What you contribute You are studying microsystems technology, physics, electrical engineering, computer science, or a comparable field. You plan and
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Competitive, interdisciplinary, and international research environment with a track record of intense mutual collaboration Structured PhD-training programme with a wide range of an professional development
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computing, and synchrotron-radiation experiments. The goal is to explore physics-informed self-supervised learning approaches (e.g., deep image priors, GANs) and iterative methods, combined with multi-scale