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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic
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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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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop 3D+t image reconstruction methods in a cell microscopy setting using image sequences as well as focus stacks
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data sets, which have to be evaluated in order to obtain a holistic understanding of very complex systems. Visit HDS-LEE at: https://www.hds-lee.de/ The position is placed at the Institute for Advanced
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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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, data science, applied mathematics, physics, materials science, or a related field. Solid background in machine learning and/or computer vision. Interest in representation learning, active learning
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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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in the 36 months immediately before your recruitment date (mobility rules of the Marie Skłodowska-Curie program) Masters degree in electrical/electronic engineering, computer engineering, computer
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date (mobility rules of the Marie Skłodowska-Curie program) Masters degree in electrical/electronic engineering, computer engineering, computer science, physics, or related fields Coursework in
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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