Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- University of Oxford
- ;
- KINGS COLLEGE LONDON
- University of London
- AALTO UNIVERSITY
- Heriot Watt University
- UNIVERSITY OF VIENNA
- University of Cambridge
- Durham University
- King's College London
- Imperial College London
- ; University of Cambridge
- City University London
- Nature Careers
- Nottingham Trent University
- Royal Holloway
- University of Liverpool
- University of Manchester
- University of Nottingham
- University of Reading
- University of West London
- 11 more »
- « less
-
Field
-
. Responsibilities include working with digital signal processing, advanced filtering techniques, dynamic feature extraction, time-domain and frequency-domain analysis, signal fusion and machine learning to enhance
-
PhD in Chemistry or a relevant subject area, (or be close to completion) prior to taking up the appointment. The research requires experience in computational chemistry, including machine learning
-
of influential knowledge leadership bringing the School together with students, business and society in learning to make a difference. Over the last five years ULMS has engaged in extensive recruitment of academic
-
interactions in the condensed phase and at surfaces, with a particular emphasis on the development and application of first principles and/or machine learning approaches. Research in the Michaelides group
-
projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification
-
, Synthetic Data for Machine Learning in Privacy Research, Formalization of Security Risk Management, and Security and Privacy of Blockchain Technologies. In the long term, we are concerned with understanding
-
Essential Criteria: Qualifications A good first degree in Computer Science, Machine Learning, Maths and Statistics, Robotics or a related subject. A PhD (or an MSc with extensive research experience) in
-
and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high
-
, the Leonardo engineers involved in the project, and Dr Sam Tammas-Williams and Prof Jonathan Corney from University of Edinburgh. They will also work with PhD students and the other PDRAs of the Prosperity