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 Birmingham
- University of Sheffield
- ;
- Bangor University
- KINGS COLLEGE LONDON
- The University of Manchester;
- University of Cambridge
- University of Cambridge;
- University of Warwick
- Edinburgh Napier University;
- Oxford Brookes University
- The University of Edinburgh
- University of Birmingham;
- University of Bristol
- University of East Anglia;
- University of Exeter
- University of Nottingham;
- University of Oxford
- University of Sheffield;
- University of Surrey
- ; Coventry University Group
- ; The University of Manchester
- ; University of Exeter
- European Magnetism Association EMA
- 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;
- UCL
- Ulster University
- University of Essex
- University of Leeds
- University of Liverpool
- University of Newcastle
- University of Warwick;
- 36 more »
- « less
-
Field
-
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 their PhD
-
control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
-
processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
-
the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
-
to learn laboratory methods for analysis of relevant BGC parameters. Training: You will be based in the Polar Oceans Team at British Antarctic Survey, a highly active research team focused on both
-
spectroscopic methods suitable for large-scale sample screening and eventual field deployment. The project will also involve developing your skills in data science, including multivariate analysis, machine
-
measurement; Measurement of related tracers (e.g., Radon); Programming (e.g., R, Python) for advanced atmospheric time-series analyses, including machine learning; Skills for presenting research at scientific
-
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