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functions to work properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellowship in Volcano Climate Modelling Apply
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this we will be creating agentic AI models and in a joint effort between the Research Group for Genomic Epidemiology at DTU National Food Institute and Section of Epidemiology, Department of Health, UCPH we
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modeling and simulation, and statistical inference (lead by mathematicians and biologists) - The recruited postdoc will be asked to work in the labs on a daily basis. - The recruited postdoc will be expected
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referrals Document student conduct concerns and collaborate with supervisor on resolution strategies Serve as a positive role model for community standards and expectations Facilitate conflict resolution
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in particular artificial intelligence (AI)—to study genetic and epigenetic alterations in cancer. ICGI is recognised for its work in digital pathology, where AI is used to develop new models
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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, in CPDM Laboratory (Physico-Chemical Behaviour and Material Durability) and EMGCU (Experimentation and Modelling in Civil and Urban Engineering), in MAST Division (Materials and Structures
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html Department Description The mission of the department of Community Health Systems (CHS) is to
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in exposure-based CBT, consistent with the PATCH treatment model, as well as use evidence-based assessment progress monitoring tools to guide their treatment practice. The individual also will support
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Description Join the NWO Perspectief FIND program and develop methods to adapt Transformer-based foundation models for defect detection where data is scarce and unlabeled. Explore few-shot learning, self