Sort by
Refine Your Search
-
Listed
-
Employer
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Nottingham
- UNIVERSITY OF SOUTHAMPTON
- University of Birmingham
- University of Manchester
- University of Oxford
- Cranfield University
- King's College London
- Nature Careers
- Queen's University Belfast;
- The University of Southampton
- UNIVERSITY OF SURREY
- University of Leeds
- University of London
- CRANFIELD UNIVERSITY
- De Montfort University;
- UCL;
- AALTO UNIVERSITY
- Cranfield University;
- Imperial College London
- King's College London;
- London School of Hygiene & Tropical Medicine;
- Manchester Metropolitan University
- Oxford Brookes University;
- QUEENS UNIVERSITY BELFAST
- The Francis Crick Institute;
- The University of Edinburgh;
- The University of Manchester;
- Ulster University;
- University College London
- University of Aberdeen;
- University of Bath
- University of Birmingham;
- University of Brighton
- University of Hertfordshire;
- University of Surrey
- University of Sussex;
- University of the West of England
- 28 more »
- « less
-
Field
-
, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning
-
of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical systems. Key Responsibilities Derive and analyse closed-form mathematical
-
-focused engineers to contribute to our successful railways-applied smart machines research programme. About the Role We are seeking a highly motivated and multiskilled Research Fellow with expertise in
-
of the following: cancer biology / cancer immunology / epithelial cell biology / evolutionary biology / genomics / statistics / mathematics or machine learning* Technical qualifications: For bench
-
processing and statistical machine learning techniques to mine self-reports and sensor data to gain new insights towards assessment and longitudinal monitoring of bipolar disorder; Work on sleep datasets
-
, microbial cultures, and cleaning validation samples. Develop data analysis pipelines for Raman spectral classification, potentially integrating machine learning methods. Research & Project Responsibilities
-
to £43,805 per annum Apply by: 26/04/2026 Role Description We welcome applications from skilled, delivery-focused engineers to contribute to our successful railways-applied smart machines research programme
-
to £43,805 per annum We welcome applications from skilled, delivery-focused engineers to contribute to our successful railways-applied smart machines research programme. About the Role We are seeking a highly
-
analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during
-
for light–matter interaction in hyperuniform disordered plasmonic structures, including electromagnetic modelling, optimisation of metal–dielectric–metal resonators, and physics-informed machine-learning