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, and datasets; often at substantial computational and environmental costs. This PhD project targets sustainable and resource-efficient machine learning with a focus on methods that reduce compute, energy
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or other large-scale biological data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on single-cell
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aimed at developing novel Artificial Intelligence–based methods and software to assist physicians with: Disease classification Treatment decision support What-if analyses. Although the developed methods
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translational medicine, improving diagnostics and healthcare solutions. For more information, please visit our page . Your role We are looking for a highly motivated PhD candidate interested in AI-based methods
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meet the formal requirements for admittance to the Faculty of Social Sciences’ PhD program. The Master’s degree must be within a specialization of relevance to innovation studies and related fields
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
1.309,64 €, being the payment method by Wire Transfer. Eligibility criteria Admission Requirements: To be enrolled at a PhD. Holders of a Master’s degree in Architecture. A minimum of two years of experience
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look forward to receiving your application! We are looking for a PhD student for sustainable and resource-efficient machine learning. Your work assignments Machine learning has recently advanced through
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ICT Services & Applications. Your role The PhD position is part of the CART-4D project, a "Made in Luxembourg" collaboration between the University of Luxembourg and ARSPECTRA . The doctoral candidate
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Biological sciences » Other Medical sciences » Epidemiology Medical sciences » Health sciences Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Mar 2026 - 23:59
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” sessions to wrap up the week. These formal and informal occasions provide opportunities to exchange ideas, celebrate milestones, and strengthen connections. PhD candidates also arrange social activities