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-learning based vision pipelines to preprocess, segment cells and perform phenotype classification and regression on a variety of microscopy images. You will deal with images from multiple microscopy domains
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imaging cameras in advanced silicon technologies. Your work will push the boundaries of high-frequency sensing and integrated EM design. Job description In the Tera-Hertz Sensing (TS) Group at TU Delft, you
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. To this end, the lab has developed a technique for imaging spin waves – microscopic waves in magnetic materials - based on magnetic sensing with nitrogen-vacancy (NV) spins in diamond. Spin waves could enable
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will image them using a variety of microscopy methods, and collaborate with a team of computer vision scientists to build ML-based models for phenotype prediction, helping to accelerate the cell
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assess their usefulness. Co-create a regional risk picture by facilitating workshops to prioritise event–disruption–risk combinations with compounding impacts on care (e.g., precipitation extremes
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. Reporting: Communicate findings to project partners with diverse backgrounds (e.g., space systems engineering, astrobiology, microfluidics) to support the development of a prototype LMCOOL instrument for
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-efficient artificial intelligence (AI) applications. However, this new computing paradigm faces various design challenges in terms of design and technology challenges, application mapping and reliability
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into this environment are invited to apply. Experience in fields such as microfabrication, nanofabrication, biophysics, single-molecule techniques, synthetic cells, and optical imaging is welcomed. We foster diversity
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international level. Candidates that fit into this environment are invited to apply. Experience in fields such as NPC, DNA origami, IDPs, MINFLUX, biophysics, single-molecule techniques, and optical imaging is