Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Cranfield University
- Technical University of Denmark
- ;
- Curtin University
- Nature Careers
- RWTH Aachen University
- Roma Tre University
- Vrije Universiteit Brussel
- ; Swansea University
- Aristotle University of Thessaloniki
- Cornell University
- DAAD
- GFZ Helmholtz Centre for Geosciences
- ICN2
- KNAW
- La Trobe University
- Technical University of Munich
- The Ohio State University
- University of Southern Denmark
- University of Texas at Tyler
- Wageningen University and Research Center
- ; Cranfield University
- ; The University of Manchester
- ; University of Nottingham
- ; University of Reading
- ; University of Southampton
- AIT Austrian Institute of Technology
- Delft University of Technology
- Duke University
- Fred Hutchinson Cancer Center
- Friedrich Schiller University Jena •
- Ghent University
- Hannover Medical School •
- Hertie School •
- Indiana University
- Leiden University
- Linnaeus University
- Ludwig-Maximilians-Universität München •
- Lulea University of Technology
- Monash University
- Murdoch University
- NTNU - Norwegian University of Science and Technology
- Norwegian Meteorological Institute
- Osnabrück University •
- Technical University Of Denmark
- Texas A&M University
- The University of Iowa
- UNIVERSITY OF MELBOURNE
- Universidade de Coimbra
- University of Adelaide
- University of Bergen
- University of Bristol
- University of British Columbia
- University of Göttingen •
- University of Minnesota
- University of Münster •
- University of Nottingham
- Yeshiva University
- 48 more »
- « less
-
Field
-
CSIRO IPhD Scholarship - AI-empowered visual recognition system for dairy cow identification, health and behaviour monitoring and detection The CSIRO Industry PhD Program (iPhD) is a four-year
-
deep learning. The purpose of this scholarship is to support a PhD student to contribute to the advancement of infrastructure monitoring technologies with strong industry collaboration. Student type
-
The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack
-
scientific discoveries to improve human health locally and around the globe. Composed of more than 2,600 faculty physicians and researchers, nearly 2,000 students, and more than 6,200 staff, the Duke
-
improves the performance of ROMs, making them more applicable to real-time structural health monitoring, vibration analysis, and control design. This research offers real-world impact across several
-
monitoring and health monitoring of the different machine components. To this end, multiple dedicated measurement campaigns have been performed throughout the Belgian offshore zone, resulting in a large in
-
Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
-
engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
-
Job Description Are you passionate about transforming food safety through cutting-edge technology and want to apply your data science and AI skills to real-world public health challenges? This is
-
Supervisors: Dr Katherine Finlay, Psychology (Lead) Collaboration Partners: Dr Alexandra Oti, Unravel Health Dr Chanais Matthias, Manchester Metropolitan University Project Overview: Hormone-driven