94 phd-position-in-data-modeling-"Prof"-"Prof.-Dr"-"University-of-Strathclyde" Fellowship positions
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Peking University, Kavli Institute for Astronomy and Astrophysics Position ID: Peking University-Kavli Institute for Astronomy and Astrophysics-KOHEI2025 [#30668] Position Title: Position Type
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The position is funded by the Open Philanthropy grant “Verifiably Robust Conformal Probes”. The project’s goal is to develop methods for latent probing (aka activation monitoring) of large language models (LLMs
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The position is funded by the Open Philanthropy grant “Verifiably Robust Conformal Probes”. The project’s goal is to develop methods for latent probing (aka activation monitoring) of large language models (LLMs
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Job Description Position Details Department of Microbes, Infection and Microbiomes, School of Infection, Inflammation and Immunology, College of Medicine and Health Location: University
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project, so it promises to be a very exciting time to join our team! Successful candidates will have a PhD degree in a relevant field, expertise in processing and modelling geodetic data using open-source
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Qualifications: PhD awarded within 3 years in business administration, computer science, information systems, data science, biomedical engineering, or a related discipline. Programming & Data Skills: Strong
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teaching assistant at UiT (25% of the PhD time) Finally, writing up and defending a PhD thesis. Want to know more about the position? For further information about the position, please contact: Associate
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teaching assistant at UiT (25% of the PhD time) Finally, writing up and defending a PhD thesis. Want to know more about the position? For further information about the position, please contact: Associate
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responsibilities The Research Fellow/Senior Research Fellow will: Lead GBD research projects, which may include systematic reviews, meta-analyses, and epidemiological disease modelling. Set research direction and
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hours to a few days) are difficult owing to model and data limitations, the importance of extremes and anomalies, as well as the need to appropriately blend physics with AI. 2. Theme 2 (“Downscaling