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the Netherlands, in an international and open working environment. Selection process For more information about the position, please contact Dr. Fons van der Plas, [email protected] ; Dr. Philippine Vergeer
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machine learning or computer vision models Technical competencies in one or more of the following: bio-digital systems, biodesign, applied machine learning, computer vision, computational biology, and/or
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ambition is to move beyond disease-specific approaches by identifying biological, behavioural and digital markers that can help characterise clinically meaningful processes across different health conditions
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27 Sep 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
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ingredients, a process that is traditionally slow because each substrate–strain combination behaves differently. By applying machine learning to historical experimental data, we can predict high‑potential
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the project, you will develop and optimize printable materials and fabrication processes for creating conductive tracks, electrodes and other electronic components within soft 3D structures. You will
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vision, robotics and radar, such as NeurIPS, CVPR, ICRA, IEEE IV and RadarConf. For your research, you will have access to extensive computing resources at TU Delft, ranging from personal workstations and
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to your needs. This way, we encourage you to grow in what you do, both in your work and your development. Read more about our terms of employment . Selection process At Utrecht University, we strive to be a
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have: MSc in engineering or similar discipline by the start date of the position Experience with mechanical modeling and simulation Experience in computer programming/scripting (e.g., C++, Python, Matlab
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to backward erosion piping. You will investigate how this approach can be further developed to capture the physical processes that govern pipe formation and progression, while connecting detailed modelling with