Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Zintellect
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Nanyang Technological University
- Northeastern University
- Carnegie Mellon University
- NTNU - Norwegian University of Science and Technology
- UNIVERSITY OF SURREY
- University of British Columbia
- University of Oslo
- Ellison Institute of Technology
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- UiT The Arctic University of Norway
- University of Michigan
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- Bowdoin College
- Central Michigan University
- INESC TEC
- Johns Hopkins University
- King Abdullah University of Science and Technology
- Macquarie University
- Max Planck Institute of Biochemistry, Martinsried
- NTNU Norwegian University of Science and Technology
- National University of Singapore
- UNIVERSITY OF HELSINKI
- University of Algarve
- University of Kansas Medical Center
- University of Sydney
- University of Texas at Austin
- Birkbeck University of London
- Birkbeck, University of London;
- Cornell University
- Dalhousie University
- Durham University
- ETH Zürich
- Florida Atlantic University
- Florida International University
- Harvard University
- INESC ID
- Imperial College London
- MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA
- Mayo Clinic
- National Research Council Canada
- Singapore University of Technology & Design
- Technical University of Munich
- The Francis Crick Institute;
- UCL;
- UNIVERSITY OF SYDNEY
- University of Agder
- University of Birmingham
- University of Helsinki
- University of Michigan - Flint
- University of New South Wales
- University of North Carolina at Chapel Hill
- University of Science and Technology of China
- University of Sheffield
- University of Surrey
- University of Texas Rio Grande Valley
- University of Turku
- University of Tübingen
- Visterra, Inc.
- 50 more »
- « less
-
Field
-
intelligence, including machine learning and computer vision, robotics, and physics-based modelling, the DISC Lab pioneers new methods for monitoring, digitalization, and automation in construction. We
-
particular emphasis on integrating satellite LiDAR and UAV data with field observations. Applying statistical modelling, automated machine learning approaches, and artificial intelligence for the analysis and
-
, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural
-
fields such as computer vision and natural language processing, graph-structured data remain a rich frontier for methodological innovation, with many fundamental challenges and exciting opportunities ahead
-
scales, from the genome to the continent, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning
-
machine-learning, predictive-modelling or multivariate methods to behavioural and/or EEG data. Proficiency in R, MATLAB and Python. What we can offer In return we offer a generous pension, relocation
-
of molecular data. While machine learning has transformed fields such as computer vision and natural language processing, the molecular life sciences remain a rich frontier for methodological innovation
-
should possess: PhD/Ms/BSc in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep
-
for: Conducting research and development on AI-based solutions for automated defect inspection and condition assessment of train components by designing and developing deep learning, computer vision, and machine
-
Digital Provenance Research and Collection Histories Computer Vision for Art Historical Research Cultural Analytics and Network Analysis Geospatial Approaches to Art History Supervision The Fellow will also