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to support personalized lifestyle interventions and clinical decision-making for chronic disease management. Perform large-scale data integration and analysis, ensuring data quality, security, and compliance
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reviews Lead the analysis of large-scale population level data sets using statistical and data science techniques Provide statistical and mathematical modelling advice to junior researchers Lead the writing
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 8 hours ago
collaborate with FDA scientists to compile immunogenicity assessment data from multiple regulatory sources, including Biologics License Applications (BLAs), validation reports, and clinical pharmacology review
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8 Feb 2026 Job Information Organisation/Company University of Oslo Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Mar
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timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization? We are particularly interested in: LLM-driven
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. Where to apply E-mail bolsas@inesc-id.pt Requirements Research FieldEngineering » Computer engineeringEducation LevelMaster Degree or equivalent Additional Information Work Location(s) Number of offers
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5 Mar 2026 Job Information Organisation/Company University of Oslo Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 8 Mar
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factors for Alzheimer’s disease and related dementias by integrating large-scale human genetic data with phenotypic, environmental, lifestyle, and registry-based information. The postdoctoral fellow will
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10 Feb 2026 Job Information Organisation/Company Instituto Superior Técnico Department Direção de Recursos Humanos Research Field Engineering » Maritime engineering Researcher Profile First Stage
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better subsurface understanding, uncertainty quantification, and robust forecasts suitable for emissions reduction, increased energy efficiency, and recovery improvements with large amounts of data