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Field
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are looking for a PhD candidate to develop and evaluate a mathematical model and algorithm to better tailor (risk-based) follow-up after cancer treatment. The role is highly impactful for ensuring sustainable
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specific focus on financial markets and systems. Students will engage with predictive modeling, machine learning algorithms, and statistical analysis tailored for environments where data is continuously
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reliable comparative database. Finally, the candidate must be able to develop and apply classification algorithms for discriminating between asbestos-cement roofs. Where to apply Website https://xup
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algorithms, and their experimental validation in teleoperation scenarios. Where to apply Website https://trasparenza.uniroma1.it/ Requirements Additional Information Eligibility criteria Eligible destination
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clinical decision support tool for patients with atrial fibrillation, and directly utilizing the specific decision-support device (based on AI algorithms) developed during the study in accordance with
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highly valued. Ability to collaborate well with a team, and experience working in a university environment. Foundational understanding of data structures, algorithm design, or object-oriented. Experience
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have submitted your thesis and be awaiting viva. Essential criteria include experience of conducting and publishing high-quality AI research, strong knowledge of AI algorithms, programming experience in
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research across a wide range of disciplines including mathematics, the sciences and computer science, with an emphasis on the theoretical foundation of machine learning, new algorithms and AI for Science
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of research may include, but are not limited to, digital media culture, material media studies, media production studies and digital labour; datafication, algorithms and artificial intelligence in media
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of search algorithm changes (including AI-driven search/LLM discovery shifts) and adjust strategy and university education around these shifts proactively. Cross-Functional Collaboration & Governance Serve as