Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of East Anglia
- University of Nottingham
- AALTO UNIVERSITY
- Loughborough University
- The University of Manchester
- University of Sheffield
- ;
- Bangor University
- The University of Manchester;
- University of Birmingham
- University of Cambridge
- University of Cambridge;
- University of Warwick
- Edinburgh Napier University
- KINGS COLLEGE LONDON
- Oxford Brookes University
- University of Birmingham;
- University of Bristol
- University of East Anglia;
- University of Nottingham;
- University of Sheffield;
- University of Surrey
- ; Coventry University Group
- ; The University of Manchester
- ; University of Exeter
- Harper Adams University
- King's College London
- King's College London;
- Liverpool John Moores University
- Loughborough University;
- Manchester Metropolitan University;
- Nature Careers
- Newcastle University
- The University of Edinburgh
- The University of Edinburgh;
- UCL
- University of Essex
- University of Exeter
- University of Leeds
- University of Newcastle
- University of Oxford
- University of Warwick;
- 33 more »
- « less
-
Field
-
treatment processes through advanced machine learning, validated against physics-based models and experimental data. System Integration: Integrating the DTs into material and energy balance equations
-
University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
-
sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms
-
with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
-
your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had
-
PhD: Systematic Exploration of Robot Behaviours for Manufacturing Tasks to Automatically Discover Failure Scenarios EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering
-
focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
-
may also explore embedding these new computational methods into optimisation and machine learning contexts. The new computational techniques developed will be geared towards the following key
-
. Fe, S) on CNT purity and structure. Evaluate CNTs as conductive additives in standard Li-ion battery electrodes. Apply AI/machine learning to optimise experimental design and growth parameters
-
experience includes: Nano-imaging or sensing methods Optical or vibration detection technologies AI/machine learning for imaging and sensing Background in biology, microbiology, or biomedical sciences