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matter (or other “invisible” new physics signals) at the Large Hadron Collider (LHC) compare high-dimensional collision data against detailed simulations whose likelihood cannot be evaluated, only sampled
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statistical software & machine learning (e.g., R, Python, SAS, or STATA). Experience working with large population dataset (e.g. EHR, claims data). Background in health informatics, population health research
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concordance and adverse health outcomes using large -scale healthcare datasets. Working collaboratively with clinicians, researchers, patient partners and data specialists to ensure scientific quality and
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Required: Ph.D. in high energy nuclear or particle physics or a related field Required Qualifications: Demonstrated experience in data analysis. Skill related to the analysis of large-scale datasets (e.g
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19 Sep 2026 Job Information Organisation/Company Utrecht University Research Field Agricultural sciences » Phytotechny Agricultural sciences » Soil science Biological sciences » Biodiversity
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a Ph.D. degree in Health Science, Public Health or Geriatric Science, preferably with experience in health service research, advanced data analytics, digital health innovation, and/or big data
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including causal inference and prognostic/risk prediction modelling. It will be essential to have evidence of strong data management skills and experience managing large linked administrative datasets using
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. Ongoing projects leverage large-scale multimodal clinical data, including electronic health records (EHRs), medical imaging, genomics, wearable devices, and unstructured clinical text, to develop novel
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, biomonitoring, and toxicity data. Key responsibilities: Lead UCAM's contribution to Task 5.2, including modelling of respiratory deposition of indoor particulate matter and estimation of exposure to aerosol-bound
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Systems and Software Program (WASP ). You can find more information about us on the Department of Information Technology website. The position is hosted by the Division of Scientific Computing (TDB), one