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of results in scientific journals Requirements PhD in Physics, Engineering, Economics, Environmental Sciences, Mathematics, System Sciences or a related field training in formal, quantitative methods
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- Familiarity with method development, data processing software, and QA systems - Knowledge of ISO17025 accreditation processes - Good English communication skills (written and verbal) - Experience with sample
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of results in scientific journals Requirements: PhD in Physics, Engineering, Economics, Environmental Sciences, Mathematics, System Sciences or a related field training in formal, quantitative methods
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methods and software for the analysis and calibration using very large data sets resulting from dynamical simulations on high-performance computing resources. Application areas include : 1. Epidemiology, 2
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to develop innovative methods and actionable tools for detecting, analyzing, and preventing vulnerabilities in supply chain systems, leveraging state-of-the-art AI and ML techniques to improve overall security
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health economic impact. Further detail: We have demonstrated proof of concept on the lab bench of a UV ‘elucidation’ method. This identified previously missed bone fragments that had passed manual
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-mentioned methods Provide guidance to PhD students Disseminate results through scientific publications Prepare research proposals to attract industry partnerships as well as national and European grant
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experience in machine learning methods, tools, and platforms. Proficiency in Python, with demonstrated software development experience. Hands-on experience in MLOps, including the design and deployment
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disparities for communities and populations. Candidates will receive mentorship and training in precision health, including advanced statistical methods focused on predictive modeling in relation to response
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outlined in the project description. Applicants to the PhD fellowship must hold a two-year Master’s degree (or equivalent qualifications) and meet the formal requirements for admittance to the Faculty