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large-scale speech and wearable data from participants in the GLAD Study cohort ( https://gladstudy.org.uk/ ). Using large language models (LLMs) and acoustic analytics, they will uncover patterns in
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Posting Details Student Title Classification Information Quick Link https://chapman.peopleadmin.com/postings/37947 Job Number SE144024 Position Information Department or Unit Name Career and
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to learn about fundamental particles and their interactions, by analyzing data obtained from the CMS experiment at the Large Hadron Collider (LHC) located at CERN, Switzerland. The pool of mentors
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, preferably two years. Ph.D. training in clinical pharmacy, social & administrative pharmacy, pharmacy education, or pharmacy informatics/big data analysis. Experience in pharmacy practice Demonstrated ability
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. The successful candidate will be involved in analysing data from patients with rheumatoid arthritis as part of a large international study funded by the European Union: PerPrev-CID (Personalised Disease Prediction
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Centre National de la Recherche Scientifique (CNRS) | Saint Aubin Routot, Haute Normandie | France | about 23 hours ago
information in the Information package for Marie Curie fellows in doctoral networks (https://op.europa.eu/s/z831 ). Selection process For the selection procedure, the SLICE consortium will appoint a
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in Experimental Particle Physics (https://www.hep.manchester.ac.uk/study/ ). Our group (https://www.hep.manchester.ac.uk/ ) is one of the largest research groups in the UK with over 100 members
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information please see the Non-Discrimination Statement at the following web address: http://uhr.rutgers.edu/non-discrimination-statement
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
descriptive, multivariate, and longitudinal data analysis using licensure data and large secondary population data sources. * Perform geospatial analysis including translating practice addresses to maps and
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-scale applications. Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI/ML, or a related field. Hands-on experience with large language models (LLMs) and AI orchestration tools