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We are seeking applicants for a 2-year postdoc in Ultrafast X-ray probes of Quantum Materials to join us at the Department of Physics and Astronomy. Starting Date and Period The position is for 2
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microscopy data analysis, chemometrics, and machine learning. This position is ideal for a researcher who enjoys working at the interface of imaging, data science, and environmental monitoring. The project
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outdoors and cultural opportunities, a vibrant student scene, and an impressive scientific heritage. Position details PhD students will have the opportunity to participate in one of several available PhD
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within the University of Münster developing imaging methods allowing to visualize molecular processes inside organisms, tissues and cells. With the help of imaging, we perform cutting-edge research in
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biomechanical data during mammalian gastrulation. This position is part of an ambitious interdisciplinary project in collaboration with Professor Shankar Srinivas (University of Oxford) and will be based in Dr
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machine learning methods are a plus. Qualifications: PhD in neuroscience, or related fields DeepLabCut or similar methods Demonstrated hands-on experience with 2-photon imaging techniques Experience
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, and deep generative models (e.g., VAEs, normalizing flows, diffusion models). Hands-on experience in multi- and hyperspectral image processing (e.g., IDL/ENVI) and RTM inversion (e.g., ARTMO
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. The postdoctoral researcher will collaborate closely with an engineering team responsible for process integration and prototype development Expected start date and duration of employment This is a 2.5–year position
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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imaging and biosensor techniques, across digital health and biological modelling, to biopharma technologies. The department has a scientific staff of about 210 persons, 130 PhD students and a technical