Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- University of Nottingham
- ; City St George’s, University of London
- ; The University of Manchester
- ; University of Nottingham
- ; Swansea University
- ; University of Exeter
- University of Cambridge
- ; University of Southampton
- ; University of Surrey
- AALTO UNIVERSITY
- Abertay University
- KINGS COLLEGE LONDON
- The University of Manchester
- The University of Manchester;
- University of Bristol
- University of Cambridge;
- University of Newcastle
- ; Brunel University London
- ; Coventry University Group
- ; Cranfield University
- ; Durham University
- ; Newcastle University
- ; The University of Edinburgh
- ; UCL
- ; UWE, Bristol
- ; University of Birmingham
- ; University of Bristol
- ; University of Greenwich
- ; University of Leeds
- ; University of Oxford
- ; University of Reading
- ; University of Warwick
- Harper Adams University
- Imperial College London
- King's College London;
- Loughborough University
- Nature Careers
- Oxford Brookes University
- The University of Edinburgh;
- UCL
- University of Birmingham
- University of Exeter
- University of Liverpool
- University of Nottingham;
- University of Sheffield
- University of Sheffield;
- University of Surrey
- University of Warwick
- 40 more »
- « less
-
Field
-
, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
-
brings together expertise in health data science, microbial genomics, and cancer bioinformatics. Th selected student will work under the supervision of Dr Arron Lacey, a specialist in machine learning and
-
Engineering, and Engineering Management. Students with interests in computational mechanics, optimization design, bioinspired design, sustainability management, machine learning, AI, uncertainty quantification
-
includes over 500m2 of studio space at UWE’s Frenchay Campus. We invite studentship applications from enthusiastic individuals who are strongly motivated to help push the boundaries of machine learning and
-
together world-class expertise in textiles, materials, soft robotics, biomechanics, sports, healthcare, machine learning and AI, with globally leading industrial and academic partners. Your Project
-
structural alloys. The project will combine advanced phase-field fracture mechanics, continuum-scale chemo-thermo-mechanical modeling, and advanced machine learning techniques for enhanced prediction accuracy
-
members of staff. Research in the Department is organised into six themes : Causality; Computational Statistics and Machine Learning; Economics, Finance and Business; Environmental Statistics; Probability
-
a growing field, with many applications in biomedical devices, electronics, and autonomous machines. Actuators to drive these robots utilise electronic, chemical, pressure, magnetic, or thermal
-
needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
-
treatment processes through advanced machine learning, validated against physics-based models and experimental data. 2. System Integration: Integrating the DTs into material and energy balance equations