Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- University of Nottingham
- ; University of Nottingham
- ; The University of Manchester
- ; University of Warwick
- University of Sheffield
- ; University of Birmingham
- ; University of Reading
- ; Swansea University
- ; University of Leeds
- ; Cranfield University
- ; Manchester Metropolitan University
- ; University of Exeter
- University of Cambridge
- ; The University of Edinburgh
- ; University of Oxford
- ; University of Southampton
- ; University of Surrey
- ; University of Sussex
- University of Newcastle
- ; UWE, Bristol
- ; University of Bristol
- Imperial College London
- University of Oxford
- ; Aston University
- ; City St George’s, University of London
- ; Loughborough University
- ; Newcastle University
- ; University of East Anglia
- AALTO UNIVERSITY
- Abertay University
- UNIVERSITY OF VIENNA
- University of Manchester
- ; Austrian Academy of Sciences
- ; Bangor University
- ; Brunel University London
- ; Coventry University Group
- ; Durham University
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Edge Hill University
- ; Midlands Graduate School Doctoral Training Partnership
- ; Queen Mary University of London
- ; Royal Northern College of Music
- ; UCL
- ; University of Essex
- ; University of Greenwich
- ; University of Hertfordshire
- ; University of Kent
- ; University of Sheffield
- ; University of Strathclyde
- Harper Adams University
- Heriot Watt University
- KINGS COLLEGE LONDON
- Loughborough University
- Newcastle University
- THE HONG KONG POLYTECHNIC UNIVERSITY
- UNIVERSITY OF EAST LONDON
- University of East London
- University of Liverpool
- 50 more »
- « less
-
Field
-
the environment and generate physically feasible motion references. Reinforcement learning allows robots to learn control strategies. This dynamic framework surpasses traditional sense-plan-act pipelines
-
to learn unfamiliar tools as needed (e.g. GitHub, APIs, new libraries). Familiarity with econometric techniques, especially panel data methods. Clear, concise written and verbal communication skills. Ability
-
-world impact of their research Be comfortable using and learning about quantitative data analysis *applicants with less experience of more advanced quantitative methods, such as computational modelling
-
/antanaviciute-group-computational-biology-and-tissue-immunology We offer • World-leading infrastructure and facilities • Opportunity to learn cutting edge molecular techniques
-
coding and CFD is advantageous but not mandatory—an eagerness to learn and innovate is key! Full training will be provided. Why This Matters Efficient storage technologies are essential for a carbon
-
code based on Modified Newtonian aerodynamics and a coupled, nonlinear thermo-structural finite element solver. Supervisors: Professor Matthew Santer, Dr. Paul Bruce. Learning opportunities: You will
-
central Manchester, the aim of this PhD project is to explore the impact of training musical performers from Global Majority backgrounds to teach children aged 6-16 from Global Majority backgrounds, and how
-
methodology to better understand the safety and performance risks. Finally, multiscale simulations will be used to map learnings from laboratory-based systems (up to10 kW) to predict the behaviour and
-
progression to PhD depending on performance during the initial period. Main duties and responsibilities Admin - ordering consumables, tracking cost and use of consumables PIL training - opportunity to acquire a
-
programming and/or CFD are desirable but not essential. The student is expected to present their research outcomes to the project team/sponsors on a regular basis in both written and oral formats. How to apply