Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- KINGS COLLEGE LONDON
- Imperial College London
- King's College London
- ;
- ; Imperial College London
- ; King's College London
- Brunel University London
- King's College London Department of Engineering
- King's College London;
- Kingston University
- Queen Mary University of London
- Royal Holloway, University of London;
- The Medicines And Healthcare Products Regulatory Agency;
- University of London
- 4 more »
- « less
-
Field
-
methods. Depending on the strengths and interests of the PhD candidates, the PhD project will focus on some of the following aspects: The quantification of the fundamental physical and kinetic differences
-
propellant space propulsion systems. A significant limiting factor of hybrid propulsion systems is the continuous change in surface area of the propellant grain during the combustion process. This changing O/F
-
platforms, and/or those proposing to use quantitative/computational methods will be given preference. Applicants are also encouraged to think about the societal impact of their research, and for example
-
, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform statistical analyses to assess stability and plasticity of multisensory
-
You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
-
Data Skills Advanced Quantitative methods Interdisciplinary Collaboration with researchers outside of the social sciences Please do speak to your selected institution should your project include any
-
framework will be used with advanced causal inference methods – including inverse probability weighting to construct a valid comparison group. The analysis will use the potential outcomes approach to address
-
visual and auditory cortices using techniques such as cross-modal decoding, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform
-
to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human
-
, and dynamic individual who is a team worker, has a positive outlook, and is adaptable and flexible in their working methods. It is also essential that you are highly experienced in setting up continuous