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Field
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. The regulation will be applied in the processing of the applications. The following applies to the PhD position About the PhD position: The fellowship will be for a period of 3 years, with the possibility for a
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uptake, stress tolerance, and species interactions. A case in point is optimal partitioning theory (OPT), a dominant paradigm of plant resource allocation that describes the ability of plants to adjust
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provides access to core equipment such as imaging, flow cytometry and other state-of-the-art tools. You will be able to develop strong working relationships with your colleagues and contribute to a stable
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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progression. The Iskratsch Group , at the School of Engineering and Materials Science, Queen Mary University of London is exploiting cutting-edge mechanobiological, as well as imaging approaches2-5 with the aim
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recognition (OCR) and handwritten text recognition (HTR) methods, while integrating recent advances in transformer-like architectures for the joint processing of text and images. Particular attention will be
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learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image analysis, that is medical images that evolve over
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the endoplasmic reticulum (ER) using multidisciplinary approaches, including proteomics, biochemistry, cellular and molecular biology, genomics, and advanced live-cell imaging. Our research focuses on identifying
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | about 2 hours ago
present your findings at internal meetings and international conferences, contribute to publications, and support a positive and collegial team culture. Essential qualifications Doctoral degree (PhD) in
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: https://www.jobbnorge.no/en/available-jobs/job/294558/phd-research-fellow-in-deep-learning-for-imaging-of-marine-ecosystems Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294558/phd