Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- European Space Agency
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- University of Twente
- Utrecht University
- University of Amsterdam (UvA)
- Erasmus University Rotterdam
- Leiden University
- Wageningen University & Research
- Radboud University
- Vrije Universiteit Amsterdam (VU)
- DIFFER
- Tilburg University
- University Medical Center Utrecht (UMC Utrecht)
- University of Twente (UT)
- ;
- AMOLF
- Maastricht University (UM)
- NIOZ Royal Netherlands Institute for Sea Research
- Nature Careers
- Radix Trading LLC
- 11 more »
- « less
-
Field
-
PhD position: Global soil mapping with process-informed machine learning Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline
-
Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking for a PostDoc who will do research on the intersection of machine learning (ML) and statistics
-
language processing, and more. We own and operate the entire technology stack for Machine Learning Operations. This ensures that the models we build translate into secure, reliable, and actionable outcomes across
-
Machine Learning, Computer Science, Mathematics, Statistics, Physics or a closely related field and want to join the mission of unlocking the “geometry of artificial intelligence” then come join us! Join us
-
Mathematics (Inverse Problems), Computer Science (Machine learning, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of the NXTGen High-tech
-
Vacancies 2x PhD positions in the Mathematical Foundations of Machine Learning on Graphs and Networks Key takeaways The Discrete Mathematics and Mathematical Programming (DMMP) group
-
Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about advancing Machine Learning by integrating
-
is looking for an aspiring PhD candidate to research causal machine learning and uncertainty quantification for Earth Observation time-series. Currently, predictive AI in Earth Sciences relies heavily
-
contribute to the development of innovative, physiology/ machine learning-driven clinical solutions and decision support tools for critically ill patients, focusing on cardiovascular and respiratory monitoring
-
Electrical Engineering, Computer Science, or a related discipline. A research-oriented attitude. Solid background in machine learning and optimization methods. Knowledge and experience in (wireless