162 machine-learning "https:" "https:" "https:" "https:" "https:" positions in Netherlands
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- Leiden University; Published today
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- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); Published yesterday
- Delft University of Technology (TU Delft); today published
- Delft University of Technology (TU Delft); yesterday published
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- Eindhoven University of Technology (TU/e); Published today
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- University of Amsterdam (UvA); Published today
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6 Dec 2025 Job Information Organisation/Company University of Twente (UT) Research Field Computer science » Informatics Computer science » Programming Engineering » Computer engineering Engineering
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://www.universiteitleiden.nl/en/science/mathematics . What you bring The successful candidate is expected to have: A master in statistics, (applied) mathematics, machine learning or a closely-related quantitive discipline (to
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specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision? Then check out the vacancy below and apply for a PhD position in this
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Management Science, Information Systems Research, and MIS Quarterly. We seek applicants with a strong quantitative background, such as analytical modeling, econometrics, and/or machine learning, and a
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experiments, behavioral research, econometric and causal inference approaches, optimization and analytical modeling, and data-driven techniques such as machine learning and large language models. Our work is
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for heavy-duty trucks, busses, mobile machines, maritime and aviation applications, focusing on battery module design and battery management system design. The group will collaborate with the leading
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. The project takes an explicit social science approach and aims to use Machine Learning and Social Network Analysis methodology to 1. analyze the current and developing opinions of new clean energy technology
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situated knowledge on corridor potentials for housing, to experiential forms of learning based on embodied experiments with alternative social practices. The conceptual and methodological approach is to
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. (2017). Beyond prediction: Using big data for policy problems. Science, 355(6324), 483–485. Barocas, S., Hardt, M., & Narayanan, A. (2021). Fairness in Machine Learning. Retrieved from https
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developers and many more, that are focused on bringing data, machine learning and statistical modeling into the products that we build for our clients or internal users. The data scientists in INGA furthermore