366 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "NORTHUMBRIA UNIVERSITY" research jobs at Nature Careers
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and a true passion for cutting-edge bench-to-bedside research are encouraged to apply and provide three professional references. LEARNING OBJECTIVES Trainees will perform basic and translational
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), combining state-of-the-art in vivo approaches with quantitative data analysis. About the lab and environment The Rebola Lab (https://therebolalab.org ) studies how variability in synaptic function across
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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information, please visit our website: https://ekfs.de/en/current-topics/call-for-proposals/else-kroner-excellence-grants-2026
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of synaptic neural circuit function Molecular, genetic and viral tools For more information about our research, visit our lab website: https://www.med.upenn.edu/fuccillolab/
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cells 4. Roles of retinoic acid and its receptor in regulation of the immune system, focusing on T and DC regulation 5. Immunotherapies and chimeric antigen receptor (CAR) therapies Lab website: https
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analysis or habitat monitoring Highly valued: Experience applying AI or machine learning methods to remote sensing data Experience with drone-based point cloud collection Experience working with or advising
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of Health (NIH) and the Department of Health and Human Services (DHHS). Within this program, the Section on Synapse Development Plasticity (Chief: Zheng Li, PhD, https://www.nimh.nih.gov/research/research
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application documents via email. To obtain an Applicant ID and download the application documents, please refer to the following URL. https://www.nims.go.jp/eng/employment/technical/permanent-researcher.html
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includes the following tasks: Develop computer-aided design software for modular construction of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models