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Field
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: MSc in materials science engineering. Backgrounds in chemistry, physics, computer science or a related area are also welcome. Good expertise or strong interest in numerical modeling, machine learning
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in Computer Science, Artificial Intelligence, or related field. Solid programming and development skills (Python, Git, Bash). Experience with machine learning (e.g PyTorch/TensorFlow). Strong interest
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biopsies and develop and validate predictive models that support and enhance personalized care. Your tasks include: Designing and conducting scientific research, with a focus on machine-learning based
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of machine learning to evaluate the predictive value of biomarkers from various sources: donor-related data, perfusion fluid, and kidney biopsies. Kidney biopsies may contain unique information about organ
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of core web technologies. You have solid experience in Python and JavaScript programming languages. You preferably have experience with building and using machine learning models. You care deeply about
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simulations. Job Description Are you passionate about bridging computational modeling with clinical cardiology to solve real-world healthcare challenges? We're seeking a PhD candidate to develop innovative
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the phenomena Identifying the fundamental variables and relationships that are most important to studying the phenomena and formalizing them in a measurement model or set of experimental hypotheses Gathering
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proactively. Experience in design, prototyping, basic programming, AI and/or machine learning are a plus. International PhD candidates with scholarships below the applicable IND income standard (currently
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theory, and machine learning. They will have access to a fully equipped lab and benefit from collaborations within the ERC team and across TU Delft. There will be opportunities to present at leading
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engineering Engineering » Design engineering Researcher Profile First Stage Researcher (R1) Country Netherlands Application Deadline 5 Oct 2025 - 21:59 (UTC) Type of Contract Temporary Job Status Not Applicable