Sort by
Refine Your Search
-
Listed
-
Employer
- ;
- Imperial College London
- University of Birmingham
- UNIVERSITY OF SOUTHAMPTON
- KINGS COLLEGE LONDON
- King's College London
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Nottingham
- CRANFIELD UNIVERSITY
- Nature Careers
- Queen's University Belfast
- The University of Southampton
- University of Oxford
- University of Bristol
- ; University of Kent
- Birmingham City University
- Cranfield University
- Manchester Metropolitan University
- QUEENS UNIVERSITY BELFAST
- University of Cambridge
- University of Leeds
- University of Liverpool
- University of London
- University of Manchester
- University of Salford
- University of Sheffield
- University of Stirling
- 17 more »
- « less
-
Field
-
: Genomics, precision medicine, bioengineering, and health data science AI and Digital: Machine learning, robotics, digital health, and cybersecurity Defence and Advanced Manufacturing: Secure systems
-
or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
-
machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role. This post would be ideal for an ambitious and
-
machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role. This post would be ideal for an ambitious and
-
cardiovascular care using advanced machine learning techniques, including deep learning. Informal enquiries may be directed to Dr. Dimitrios Doudesis, Principal Investigator (Dimitrios.Doudesis@ed.ac.uk
-
of remote sensing data using physical, statistical and/or machine learning approaches Knowledge of the latest remote sensing techniques, key satellite missions (e.g. Copernicus) and their application
-
Supervised Machine Learning and Reinforcement Learning. The objective is to significantly enhance battery performance and longevity. While conventional methods rely on either physics-based models or high-level
-
challenges from low carbon shipping and sustainable fuels to solar power technologies and advanced brain models. Learn more at https://mecheng.ucl.ac.uk . Within this dynamic environment, the Moazen Lab is
-
tools such as R, Python, or MATLAB as well as relevant machine learning frameworks Experience in statistical data analysis, and expertise in areas such as experimental design, linear/nonlinear models
-
approaches, machine learning) where appropriate. The successful candidate will actively promote FAIR data practices and will have opportunities to contribute to teaching, training, and wider community