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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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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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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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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
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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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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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chemical–biological pathway. The advertised positions will support these efforts through research on advanced carbon capture methods, process modelling and optimization, and biological CO₂ valorization in
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(SUSTAIN) research unit, the LCSA group aims to support industry, policy, and society by developing science-based, sustainability methods and computational tools for life cycle sustainability assessment
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qualification, you must hold a PhD degree in computer science, software engineering, biomedical engineering, data science, or a similar field. Your project management skills include: Experience in technical
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very good proficiency in written and spoken English is a prerequisite. The following will be considered advantages Good understanding of quantitative methods. Familiarity with established softwares