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-learning–based segmentation, classification and tracking for microbes and microgels in phase-contrast and fluorescence images Optimise these models and pipelines for real-time performance and integrate them
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on the populations phenotypic plasticity and/or genetic adaptation. As our model system, we study springtails (Collembola), key terrestrial ectothermic invertebrates of the soil community. The postdoc will be mainly
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: 87392BR Supervises staff involved in providing clinical patient care. Assists in ensuring the quality of patient care delivery in a specific patient care area and serves as a role model for professional
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research teams to develop the necessary experimental platforms, modelling and data analysis capabilities. Research Assistant Professor (25260446) Responsibilities: The Department is recruiting one scholar
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. Target start date is January 2026. Appointment Start Date: January 2026 Group or Departmental Website: https://woods.stanford.edu/ (link is external) https://sustainability-accelerator.stanford.edu/ (link
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with our Welcome Days and Welcome Guide: https://go.fzj.de/welcome FLEXIBILITY: Flexible working time models, including options close to full-time ( https://go.fzj.de/near-full-time ), allow you to
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About the ProjectProject details Self-adaptive and autonomous systems are increasingly deployed in dynamic and uncertain environments, where effective decision-making relies on accurate models
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cells and human iPS cells, as well as with genetically modified mouse and pig models. Last publications: https://pubmed.ncbi.nlm.nih.gov/40551151/ https://pubmed.ncbi.nlm.nih.gov/37967560/ https
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business problem scoping to deployment and monitoring of production-grade models-with a focus on both Generative AI and Deep Learning. The ideal candidate holds a Ph.D. in Deep Learning or Generative AI and
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Assistant Research Professor (Research Track), Radiology and Imaging Sciences Posting Number req24876 Department Radiology & Imaging Sci Dept Department Website Link https://radiology.medicine.arizona.edu