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Post-doc in Machine Learning for Image Processing on Embedded Devices (V24.0155) « Back to the overview Job description We are looking to fill a two-year postdoctoral researcher position as a part
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project will be to develop machine learning models capable of robustly classifying images of agricultural crops based on markers for health state of the crop and deploying those models on a variety of low
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project through DigiAgro3 2024. The main goal of the post-doc project will be to develop machine learning models capable of robustly classifying images of agricultural crops based on markers for health
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, implementation & fabrication of infrared capable pixels using advanced silicon post-processing technology. Your key responsibilities include: Supporting the image sensor team with mask design, device physics
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imaging of biomolecular processes in reconstituted systems and in cells. You will collaborate with leading scientists and help drive correlative high-resolution imaging at ultrafast timescales. You will
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post-processing technology. Your key responsibilities include: Supporting the image sensor team with mask design, device physics simulations and other analytical modelling Assistance with the clean room
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of computational imaging, a marriage between cleverly designed imaging systems and sophisticated post-processing. In everything we do, there is a core of cutting-edge physics and engineering of high-tech instruments
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Challenge: Ultrafast imaging of biomolecular processes at high resolution. Change: Combining single-molecule fluorescence microscopy and cryo-EM/ET. Impact: Driving a profound understanding of life
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are pioneers in developing advanced concepts of computational imaging, a marriage between cleverly designed imaging systems and sophisticated post-processing. In everything we do, there is a core of cutting-edge
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realistic ECMO groin cannulation prototype with patient-specific variations Extend the vascular tract from the neck to the right heart and the groin for physical vascular access simulation Incorporate