159 machine-learning "https:" "https:" "https:" "https:" "https:" positions in Netherlands
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- Delft University of Technology (TU Delft); today published
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology
- Eindhoven University of Technology (TU/e); Published today
- Erasmus MC (University Medical Center Rotterdam)
- Holomicrobiome Institute
- Leiden University; today published
- Maastricht University (UM)
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- NIOZ Royal Netherlands Institute for Sea Research
- Princess Máxima Center for Pediatric Oncology
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- The Netherlands Cancer Institute
- University Medical Center Groningen
- University Medical Centre Groningen (UMCG)
- University of Amsterdam (UvA); Published today
- University of Twente
- Vrije Universiteit Amsterdam
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to support coordinated decision-making for sustainable strategies in the port call? As a PhD student at TU Delft, you will leverage AI (i.e. optimization and machine learning techniques) to prepare ports
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) with quantitative techniques (e.g., computer vision, physiological sensing, environmental monitoring, crowd behaviour analysis), as well as researching existing sources of knowledge in the literature and
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Are you passionate about deep learning, generative AI, agents? We are seeking a postdoctoral researcher to join the research group led by Ivan Titov ( http://ivan-titov.org/ ), part of the natural
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top journals. Visibility at relevant international academic conferences and experience in teaching or thesis supervision (especially in data science / machine learning) are highly appreciated. Our offer
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first line treatments for OSA, and works by delivering pressurized air to keep the airway open. Traditionally, titration of optimal PAP parameters was done in sleep labs, but home titration using auto
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to travel and to participate in national and international events and conferences; proficient in general computer skills and experience with electronic collaboration tools; and willing to learn the Dutch
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enhance real-time decision-making in road traffic management. The project aims to bridge the gap between recent advances in AI and machine learning, in particular, multimodal and instruction-tuned
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natural selection acting on genes, developmental experiences, and learning in context. To illustrate, animals might exhibit anxiety in the absence of immediate threat when encounters with those threats (e.g
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wind speed and sea ice extent. The baseline algorithms designed to estimate such variables from the observed data at Level 1 (L1) are based on Machine Learning (with the exception of that for Freeze/Thaw
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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