Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- Technical University of Denmark
- Cranfield University
- ;
- Chalmers University of Technology
- DAAD
- Technical University of Munich
- SciLifeLab
- NTNU - Norwegian University of Science and Technology
- University of Groningen
- University of Southern Denmark
- Wageningen University and Research Center
- Radboud University
- Forschungszentrum Jülich
- Ghent University
- University of Göttingen •
- University of Luxembourg
- Curtin University
- Susquehanna International Group
- Linköping University
- Utrecht University
- Leibniz
- Erasmus University Rotterdam
- Monash University
- Umeå University
- University of Adelaide
- University of Sheffield
- University of Twente
- University of Tübingen
- ; Swansea University
- Fraunhofer-Gesellschaft
- Lulea University of Technology
- ; University of Birmingham
- ; University of Warwick
- CWI
- Ludwig-Maximilians-Universität München •
- Swedish University of Agricultural Sciences
- University of Antwerp
- ; The University of Manchester
- Aalborg University
- Humboldt-Stiftung Foundation
- Imperial College London
- Leiden University
- Purdue University
- University of British Columbia
- University of Oslo
- University of Utah
- Vrije Universiteit Brussel
- ; Cranfield University
- ; Newcastle University
- ; University of Reading
- Canadian Association for Neuroscience
- La Trobe University
- Norwegian University of Life Sciences (NMBU)
- Swinburne University of Technology
- The University of Chicago
- University of Bonn •
- University of Cambridge
- University of Minnesota
- University of Nottingham
- University of Stuttgart •
- VIB
- Østfold University College
- ; Technical University of Denmark
- ; University of Bristol
- ; University of Exeter
- ; University of Oxford
- ; University of Sussex
- Aarhus University
- Abertay University
- Carnegie Mellon University
- Columbia University
- Cornell University
- Dresden University of Technology •
- Duke University
- Georgetown University
- Heidelberg University
- ICN2
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Mälardalen University
- National Research Council Canada
- Queensland University of Technology
- Radix Trading LLC
- Saarland University •
- Trinity College Dublin
- University of Copenhagen
- University of Florida
- University of Manchester
- University of Massachusetts Medical School
- University of Miami
- University of Minnesota Twin Cities
- University of New Hampshire – Main Campus
- University of Newcastle
- University of North Carolina at Chapel Hill
- University of Oregon
- University of Oxford
- University of Southern Queensland
- University of Vienna
- Western Norway University of Applied Sciences
- 89 more »
- « less
-
Field
-
, and therapy resistance mechanisms Ability to work independently and collaboratively within interdisciplinary teams Prior experience with network modeling or machine learning is a plus We offer
-
strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
-
operational data and machine learning. You will be based at UCL mechanical Engineering, and collaborate with industry and port partners on system design, prototyping, and lab-based trials. Key responsibilities
-
undermine this future. Can you see how Machine Learning, Computer Vision, and Robotics can open up opportunities for autonomously operating agricultural robots? Are you passionate about making agriculture
-
We are offering a WASP, The Wallenberg AI, Autonomous Systems and Software Program, funded PhD position that provides a unique opportunity to develop deep expertise in robotics, machine learning
-
essential—what matters most is curiosity, enthusiasm, and a willingness to learn. You'll be part of a vibrant research group with strong national and international links, and have the opportunity to travel
-
geospatial data on fisheries activities near OWFs to evaluate the distributional impacts of OWFs across different fleet segments; conducting fieldwork and surveys in collaboration with ‘NO REGRETS’ partners
-
system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
-
understanding, capabilities and innovation, while inspiring and providing broad training to the next generations of researchers. Our values are Commitment, Collaboration and Transformation. Our research lines
-
innovative pedagogies such as Challenge-Based Learning and complex learning environments by fostering higher-order thinking, transdisciplinary collaboration, and active student engagement. The research takes a