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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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) 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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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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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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years post receipt of the PhD. Excellent experimental and analytical skills relevant to the project are required. Candidates with a demonstrated history of peer-reviewed publications in a related area
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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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. The analytical data is currently preliminary and incomplete. You will work with the unpublished dataset, identify data gaps and to carry out new analytical work needed to fully understand this magmatic system and
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to daily lab operations. Knowledge, Skills & Abilities: Excellent laboratory and analytical skills and commitment to scientific excellence and innovation. Knowledge of statistics and data analysis and
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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