7 control-network "https:" Postdoctoral positions at Delft University of Technology (TU Delft)
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network (based on U-net, e.g. similar to MitoNet that we used before on FAST-EM data) to automatically segment organelles from FAST-EM imaging data, with a focus on WPBs, endolysosomal compartments and
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the nacre in seashells, by combining them with soft organic polymers. This project proposes a method to mimic this by using 3D-printed concrete as a scaffold to guide the growth of a chitinous fungal network
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(for example instruments control) You have proven experience in Python development You have experience in software development and validation, especially complex simulation software Ideally, you have direct
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development of simplified continuum-based models, enabling fast assessments across large quay wall networks. This position is part of the Bridge and Quay Walls (Bruggen en Kademuren) programme of
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, from fellow academics to patients. You have experience with analysis of sensor data. You have an affinity for patient care and are able to communicate with patients. You have a good command of written
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engineering using genetic modification can solve some of these problems, but introduces regulatory complexities and biological challenges of it’s own. Epigenetic editing, the controlled reprogramming
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(Faculty of Civil Engineering and Geosciences) and work closely with Dr Louise Nuijens and an (inter)national network of collaborators. QUASI offers a unique opportunity to combine cutting edge observations