Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Eindhoven University of Technology (TU/e)
- Ludwig-Maximilians-Universität München •
- NTNU Norwegian University of Science and Technology
- Delft University of Technology (TU Delft)
- Aalborg Universitet
- CNRS
- Chalmers University of Technology
- Duke University
- Karolinska Institutet, doctoral positions
- Leibniz-Institut für Präventionsforschung und Epidemiologie – BIPS GmbH
- Linköping University
- Lulea University of Technology
- Luleå university of technology
- NOVA Information Management School (NOVA IMS)
- NTNU - Norwegian University of Science and Technology
- Nature Careers
- Princess Máxima Center for Pediatric Oncology
- Technical University of Munich
- UNIVERSITY OF VIENNA
- Universitat Autonoma de Barcelona
- University of A Coruña
- University of Amsterdam (UvA)
- University of Bergen
- University of Cambridge
- University of Massachusetts Medical School
- University of Vienna
- Utrecht University
- Wageningen University & Research
- 18 more »
- « less
-
Field
-
, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. In order to support machine learning, the project will make use of historical radar
-
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
-
Leibniz-Institut für Präventionsforschung und Epidemiologie – BIPS GmbH | Bremen, Bremen | Germany | 2 months ago
grants. Research areas of BIPS (and faculty members) include pharmacoepidemiology and cancer screening (Ulrike Haug), prevention and implementation science (Hajo Zeeb, Daniela Fuhr), biostatistics, machine
-
, currents, water levels, wind, and ice. Machine learning models will be developed to forecast future variations in such dynamic conditions and to incorporate the operational state of the vessel into routing
-
mixed models, permutational methods, Bayesian analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree