Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oxford
- University of London
- ;
- CRANFIELD UNIVERSITY
- Cranfield University
- ; University of Oxford
- University of Cambridge
- University of Greenwich
- University of Manchester
- ; Aston University
- ; Royal Institute of British Architects
- Leverhulme Trust
- Oxford Brookes University
- University of Leicester
- University of Sheffield
- 5 more »
- « less
-
Field
-
the company in Beijing. You will undertake experimental studies in the solid phase orientation of polymers to enhance their physical properties, for which we have a leading track record and facilities. The main
-
. The scheme intends to focus on developing the skills and competencies of the successful applicants and on generating practical solutions or considered recommendations that improve the physical environment and
-
, and to understand and inform the emerging international standards framework for cell and pack qualification. Eligibility This studentship is funded through the UK Engineering and Physical Sciences
-
processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability. Further details and apply
-
of the Port of Dover. The University of Manchester and Dover Harbour Board are looking to recruit a KTP Associate to undertake this 33-month project which has an overall aim of developing a physics-based and AI
-
commitment to our diverse and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability
-
the main duties will be to support the process evaluation of the CHARMER trial. This role plays a pivotal role in the important interface between the CHARMER study and external stakeholders. You will
-
to enhance sensor data accuracy and reliability in fuel tank gauging systems by developing deep learning and physics-informed deep learning models. These models will calibrate raw pressure sensor data to
-
Mary’s commitment to our diverse and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a
-
systems by developing deep learning and physics-informed deep learning models. These models will calibrate raw pressure sensor data to capacitive sensor data and incorporate flight variables to improve