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expertise in the field of prediction modeling, longitudinal data analysis, statistics, data science, machine learning, AI, organoid models and cystic fibrosis. The supervisory team will consist of dr. Maarten
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. Nice to have: Practical experience with machine-learning frameworks (e.g., PyTorch). Prior tape-out experience (ASIC or a complex FPGA prototype) and familiarity with the digital back-end flow (synthesis
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development in coordination with the interests of its scientists. As such, there are plenty of opportunities to learn new skills, expand your knowledge, collaborate across disciplines, and experiment in a
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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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or computational neuroscience/machine learning. You possess solid programming and software engineering skills. You have excellent written and spoken English skills. You are a proactive team player, who enjoys
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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
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quantitative modeling; Strong expertise in programming, including proficiency in languages commonly used in data analysis and machine learning, such as Python; Excellent verbal and written communication skills
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numerical methods, as well as familiarity with concepts in complex systems, physical memories or machine learning. We strongly believe in the benefits of an inclusive and diverse research environment, and
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analytics (statistical models, machine learning, uncertainty quantification) to monitor and predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc
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Interventions Our goal: To make digital health interventions more effective by predicting and improving adherence through Artificial Intelligence (AI) and machine learning (ML). Your colleagues