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stakeholders and external clients/sponsors. Ensure all data handling and analysis comply with stringent data security, privacy, and governance protocols. Requirements PhD degree or above in Epidemiology, Data
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Education & Experience: PhD in Computer Science, Visualization, Cartography, Geographic Information Science, or a closely related field. Strong background in visualization, computer graphics, or perceptual
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childbirth and related conditions), disability, genetic information, status as a U.S. Veteran, service in the U.S. military, sexual orientation, or associational preferences. Education Requirement: A PhD in
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to the processing of personal data for the purposes of the competition https://wppt.pwr.edu.pl/pracownicy/konkursy/wymagane-dokumenty-konkurso… (At the moment of employment) Copy of PhD degree diploma or confirmed
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) to integrate advanced AI/ML techniques into the RWE generation pipeline. Requirements PhD degree in Epidemiology, Data Science, Statistics, Computer Science, Informatics or related disciplines. Preferably
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include designing and executing experiments to interrogate host-microbe interactions, analyzing and interpreting microbiome sequencing and/or metabolomics data, developing novel computational or analytical
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Care System analytics teams, local authorities, and community partners. The role also involves contributing to data pipelines, visualisation tools, and reproducible analytical workflows, and producing
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to real-world data (RWD). Create innovative tools and solutions to extract deeper insights from RWD and enhance the centre’s analytical capabilities. Develop, validate, and deploy AI/ML models to support
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parameters. Applicants must hold a PhD degree or terminal degree from a recognized institution of higher learning with no more than five years post receipt of this degree, in Electrical/Electronics Engineering
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operating and interpreting data from analytical and characterization equipment, including: Universal Mechanical Testing Machine Scanning Electron Microscope (SEM) DTG thermal analyzer FT‑IR spectroscopy