Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Groningen
- Nature Careers
- Forschungszentrum Jülich
- Ghent University
- ;
- Technical University of Denmark
- University of Tübingen
- Cranfield University
- NTNU - Norwegian University of Science and Technology
- Linköping University
- Aalborg University
- Chalmers University of Technology
- Wageningen University and Research Center
- DAAD
- Technical University of Munich
- University of Luxembourg
- University of Stuttgart •
- CWI
- Curtin University
- Fraunhofer-Gesellschaft
- SciLifeLab
- Umeå University
- University of Southern Denmark
- University of Twente
- ; Swansea University
- ; University of Birmingham
- ; University of Bristol
- ; University of Warwick
- Aarhus University
- EBS Universität für Wirtschaft und Recht •
- ETH Zurich
- Empa
- Erasmus University Rotterdam
- Friedrich Schiller University Jena •
- Goethe University Frankfurt •
- Hannover Medical School •
- Harper Adams University
- Heidelberg University •
- KNAW
- Ludwig-Maximilians-Universität München •
- Lulea University of Technology
- Monash University
- Mälardalen University
- Norwegian University of Life Sciences (NMBU)
- OsloMet
- RPTU University of Kaiserslautern-Landau •
- Swedish University of Agricultural Sciences
- Technical University of Darmstadt •
- University of Adelaide
- University of Bamberg •
- University of Bremen •
- University of British Columbia
- University of Duisburg-Essen •
- University of Göttingen •
- University of Konstanz •
- University of Minnesota
- University of Newcastle
- University of Pittsburgh
- University of Tennessee at Chattanooga
- 49 more »
- « less
-
Field
-
training infrastructure must eventually scale beyond a single data center, requiring communication between multiple data centers over Wide Area Networks or the Internet. Such communication exposes
-
. Integrate hydraulic-hydrologic modeling and surrogate models (e.g., Bayesian Networks) to simulate stormwater behavior under future scenarios. Apply optimization techniques to design and evaluate nature-based
-
environmental inputs, algae physiological parameters and microbial community eDNA data to develop predictive mechanistic models which can be utilised to develop an optimal cultivation strategy. The project is
-
well-equipped laboratory facilities for research and a good inter-disciplinary academic network in Sweden and abroad. Subject description Machine learning focuses on computational methods by which
-
represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and