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image sequences. As a benchmark, end-to-end deep learning models will be developed using raw image data. In parallel, shallow learning models (e.g., Gaussian processes) will be explored based on insights
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imaging and single cell mass spectrometry to reveal chemical processes of importance to biological function and dysfunction. The research group has recently received major and prestigious grants
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efficient for medicine? If the answer is yes, please continue reading! Join our team! We are looking for a PhD student to work on the topic of shape analysis for medical imaging, tailored for deep learning
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, ideally with knowledge of Drosophila genetics and live imaging the applicant should be able to relocate for 6 months to our collaborator in Chile, where they will develop and optimize novel metabolite
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of porous electrodes, advanced imaging and characterization, and validation in electrochemical cells. Marie Skłodowska-Curie Doctoral Networks are joint research and training projects funded by
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, ideally with knowledge of Drosophila genetics and live imaging the applicant should be able to relocate for 6 months to our collaborator in Chile, where they will develop and optimize novel metabolite
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to the problem of thermal measurement at the nanoscale. This thesis is part of the ANTICHI (Advanced Nanoscale Thermal Imaging and CHaracterization Instruments) project, which aims to provide a versatile
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domains are e.g., signal-/image processing, artificial intelligence and machine learning. Tasks: research and development in designing and programming field programmable gate arrays (FPGAs) for accelerating
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industrial processes. Your research will drive a paradigm shift in how TES systems are modelled, integrated, and controlled within industrial settings. You will develop novel, adaptive, physics-informed models
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highly motivated PhD student to join a DFG-funded international project that investigates plant - microbiome interactions through large-scale metabolomics and other - omics platforms. Your tasks: Process