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analysis / computer vision, ideally on microscopy or time-lapse data Experience in at least one of: tracking / time-series analysis, probabilistic modelling / uncertainty, real-time or streaming pipelines
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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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a soldering station, hardware tools, as well as using a computer You are willing to expand your knowledge to cover the entire range of sample environment at JCNS You are a good team-player when it
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tasks: You will work together with renowned astrophysicists and computer scientists in the DFG-funded “Dynaverse” Excellence Cluster You will invent, implement, and benchmark novel AI tools (reinforcement
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want to hear from you! Your Job: Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant
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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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with renowned astrophysicists and computer scientists in the DFG-funded “Dynaverse” Excellence Cluster You will invent, implement, and benchmark novel AI tools (reinforcement learning, physics-informed neural
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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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Quantum Computers and JUPITER, the first Exascale computer in Europe PROFESSIONAL GROWTH: Comprehensive training courses and individual opportunities for personal and professional further development HEALTH
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on these considerations, solutions will be developed and implemented to create an advanced testing platform for the comprehensive evaluation of the long-term stability of invasive brain-computer interfaces. Your task will