Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Cambridge;
- University of Exeter
- The University of Manchester
- Newcastle University
- University of Birmingham
- University of Warwick;
- University of Oxford
- University of Cambridge
- University of East Anglia
- Manchester Metropolitan University
- University of Nottingham
- Imperial College London
- University of Warwick
- Durham University
- King's College London;
- Manchester Metropolitan University;
- University of Sheffield
- University of Surrey
- LIVERPOOL JOHN MOORES UNIVERSITY
- Royal Holloway, University of London
- University of Bedfordshire
- University of Bristol
- University of Plymouth
- City St George's, University of London (Tooting);
- City St George’s, University of London
- King's College London
- London School of Economics and Political Science;
- Newcastle University;
- Northeastern University London
- Oxford Brookes University
- South West Doctoral Training Partnership
- The Rosalind Franklin Institute
- The University of Manchester;
- University of Bath;
- University of Birmingham;
- University of East Anglia;
- University of Exeter;
- University of Liverpool
- University of Salford
- University of Sheffield;
- University of Sussex
- 31 more »
- « less
-
Field
-
, including a mixture of classical and quantum mechanics simulations, cheminformatics and machine learning, as well as collaborative software development, providing expertise for a broad range of future careers
-
of mill and production operations. The scientific challenge will be to use the model and machine learning alongside live mill data (temperature, rolling loads etc) to reverse engineer the current
-
, a strong degree in computer science, cybersecurity, mathematics, or a related subject. Experience with cryptography, machine learning, or systems implementation is valuable, as are solid programming
-
, and international studies—with cutting-edge data science techniques, including Earth Observation (EO) data analysis, machine learning, large-scale collation and analysis of survivor narratives
-
(including “The Other Kind of Doctor” podcast and blog), annual conference, and opportunities to connect and engage with PGRs outside your main discipline. Details of the Award Funding is available for 3 full
-
how machine-learning-based methods can help overcome this bottleneck, opening the door to excited-state simulations at scales and system sizes that are currently out of reach. You will work at the
-
insights for streaming, broadcast, accessibility and media production. Candidate profile Applicants should have a background in machine learning, audio engineering, speech processing or a related discipline
-
theoretical modelling. The project will focus on self-learning active mechanical networks, but will be tailored to align with the interests and expertise of the successful candidate - we will mutually ensure
-
environments where terrain can change abruptly. However, formally certifying these opaque learning-based components demands impractical resources, presenting critical safety assurance challenges and delaying
-
, machine learning, or NLP Published work in reputable conferences or journals Outstanding academic performance in relevant modules or degrees A strong motivation to work on cutting-edge research in Agentic