Sort by
Refine Your Search
-
Category
-
Employer
- Cranfield University
- ;
- ; The University of Manchester
- University of Nottingham
- ; University of Warwick
- ; City St George’s, University of London
- ; University of Nottingham
- ; Swansea University
- ; University of Exeter
- ; University of Leeds
- ; Loughborough University
- ; Newcastle University
- ; University of Bristol
- ; University of Southampton
- ; University of Surrey
- Abertay University
- Imperial College London
- University of Cambridge
- ; Aston University
- ; Brunel University London
- ; Coventry University Group
- ; Cranfield University
- ; Durham University
- ; The University of Edinburgh
- ; UWE, Bristol
- ; University of Copenhagen
- ; University of East Anglia
- ; University of Greenwich
- ; University of Strathclyde
- ; University of Sussex
- Harper Adams University
- University of Newcastle
- 22 more »
- « less
-
Field
-
together world-class expertise in textiles, materials, soft robotics, biomechanics, sports, healthcare, machine learning and AI, with globally leading industrial and academic partners. Your Project
-
candidate will have strong analytical skills and substantial experience in machine learning at scale. The Prorok Lab in the Dept. of Computer Science & Technology, has a variety of robotic platforms (aerial
-
the solution of governing PDEs. - Train machine learning models to predict lifetime and failure based on loading and environmental histories. The PhD student will have access to world-class computing facilities
-
which there exists extensive experience in the areas of machine learning, biostatistics, and medicine: Dr Yanda Meng and Dr Tianjin Huang (Machine Learning), Prof Yalin Zheng (AI in Healthcare), A/Prof
-
energy; thereby minimising farming’s environmental impact. AI machine learning offers a new expedient method of developing control systems for tasks that would be difficult to manage using classical
-
AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
-
/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
-
, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Strong background/skills on machine learning, mathematics, probabilistic
-
We are seeking a highly creative and motivated Postdoctoral Research Assistant/Associate to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK. This
-
Closing Date: 15 August 2025 Eligibility: UK Only Funding: Joint School of Civil Engineering/EPSRC Doctoral Landscape Award Studentship, providing the award of full academic fees, together with a