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Field
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. More generally, the PhD thesis is part of a large initiative at Serval and SnT, which aims to support the reliable deployment of machine learning systems by providing industry actors with practical tools
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-wide traffic prediction Design physically consistent and interpretable machine-learning methods for dynamic traffic systems Test and validate prediction models using large-scale real-world traffic data
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data • Design clinically meaningful benchmarks and robust evaluations • Publish at leading machine learning and medical AI venues • Collaborate with clinicians, computer scientists, and European partners
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analysis, causal inference with machine learning, and deep learning for various health-related domains. The Global Pathogen Analysis Platform (GPAP) is a new international initiative to strengthen global
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15 Aug 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Programming Engineering » Computer engineering Engineering » Electrical
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field. Strong foundations in machine learning and familiarity with current AI tools and practices. A solid understanding of large language models, in particular their reliability, security, and
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limited available. In this PhD project, you will help develop the first blood-based test for ANOCA, combining next generation sequencing, multi-omics analyses, and advanced machine learning to diagnose
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of machine learning and clinical oncology, with access to a large multimodal research dataset, substantial GPU resources, and a collaborative scientific environment. Your tasks Design and implement LLM-based
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infrastructures. • Experience in advanced statistical analysis and the processing of large volumes of data. • Participation in international scientific collaborations. Complementary Training • Knowledge of machine
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of flexible energy resources (e.g., heat pumps); knowledge of mathematical modelling, optimization, machine learning, or data analytics (experience in one or more is desirable); strong scientific programming