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- Eindhoven University of Technology (TU/e)
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); Published yesterday
- Maastricht University (UM)
- Radboud University Medical Center (Radboudumc)
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and scalable. Design and build a technology demonstrator prototype of clinical-testing grade. Collaborate with interdisciplinary teams, including clinicians, engineers, and machine learning (ML) and
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stimulating, interdisciplinary environment. develop and validate machine learning models to extract digital biomarkers for atypical parkinsonism from real-world wearable sensor data. interpret findings in close
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering
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. Until now, specific EN fingerprints of localized corrosion are determined manually. This is a tedious procedure that requires considerable expert knowledge. Artificial intelligence or machine learning (AI
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First Stage Researcher (R1) Country Netherlands Application Deadline 10 Dec 2025 - 22:59 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU
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based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored, and the findings of your project will be
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-on monitoring with cutting edge data-driven and physical based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored
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: vibration measurement and analysis, AI/machine learning or signal processing Programming experience (e.g. Python, MATLAB, or similar) A creative and analytical mindset with an eagerness to pioneer new methods
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these sounds fascinating, then this PhD position is made for you! Information We invite highly motivated students with a strong background in mathematical control theory, and a keen interest in machine learning
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at TU Delft. In this project we also work together with experimental groups at TU Delft and beyond. The Delft Bioinformatics Lab has strong algorithmic and machine learning expertise, with a profound