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, explainable AI (XAI) analysis and data-flow mapping, on welfare-AI systems in the UK, Netherlands and Sweden, contributing to comparative insights and high-quality project outputs. They will collaborate across
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of Position Other Position Time Status Full-Time Required Education PhD in Microbiology, Molecular Biology, Biochemistry, or a related field Required Related Experience Demonstrated experience working with RNA
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modelling. Experience in analysing ecological monitoring data (e.g. telemetry, diet and population datasets). Advanced programming skills (R, Python, or equivalent) and reproducible analytical workflows (e.g
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, machine learning, or data analytics. As a proficient programmer (ideally Python), you will be curiosity-led, with exceptional communication skills, and thrive in a highly interdisciplinary environment. You
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sites; (20%) • Conduct analytical work at Duke labs to analyze the chemical and isotopic compositions, of rocks, waste rocks, tailings, groundwater, surface waters; (30%) • Evaluate data, write
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Hutch Cancer Center and to contribute to a growing ecosystem in data science and health analytics. Responsibilities Conduct original methodological research in statistics, machine learning, epidemiology
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performance should improve over time as more data becomes available. The diagnostic conclusions will be presented to an operator using a combination of AI-based fault isolation algorithms and data-driven
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other activities to promote a strong multi-disciplinary and international network between PhD students, postdocs, researchers, and industry. This project is established in collaboration between LTU and
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mission data, including AI, analytics and digital twins; new ways to define and model systems, such as model-based system engineering; supervision of on-board autonomy featuring AI, in relation
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, bioinformatics, analytical chemistry (LC-MS, HPLC), and microbial genetics Ability to analyze, publish, and present research data Self-motivation, ability to work independently and collaborative within a team