Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oxford
- KINGS COLLEGE LONDON
- ;
- AALTO UNIVERSITY
- King's College London
- Heriot Watt University
- UNIVERSITY OF VIENNA
- University of London
- ; Technical University of Denmark
- Durham University
- Imperial College London
- King's College London;
- Medical Research Council
- Nature Careers
- Northumbria University;
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Technical University of Denmark
- University of Cambridge
- University of Cambridge;
- University of Lincoln
- University of Manchester
- University of Reading
- University of Sheffield
- University of West London
- 14 more »
- « less
-
Field
-
and Machine Learning (ECU, Perth, AU) and the School of Psychiatry and Clinical Neuroscience (UWA, Perth, AU). Importantly, we adopt a flexible working environment within the lab and are happy
-
(KCL, London, UK) but will also have the opportunity to travel and work at the Centre for AI and Machine Learning (ECU, Perth, AU) and the School of Psychiatry and Clinical Neuroscience (UWA, Perth, AU
-
About the Role We are seeking an enthusiastic and motivated postdoctoral researcher to apply advanced data analytics and machine learning techniques to real-world clinical data in the field of viral
-
networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with
-
experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
-
in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to adel.bibi@eng.ox.ac.uk For more information about working at
-
on a new project called TRUSTLINE, which is part of the Learning Introspective Control (LINC) DARPA Program. The project aims to develop machine learning (ML)--based introspection and monitoring
-
analysed by bespoke machine-learning driven algorithms, combined with physical models, to de-noise images, identify features and correlate properties, giving critical insights into power loss pathways
-
machine learning, computer vision, human-computer interaction, or similar relevant areas. Experience in research or development on bias, interpretability, and/or privacy in machine learning/AI is necessary
-
) in machine learning or a closely related field you should possess sufficient specialist knowledge in the discipline to work within established research programmes and have an ability to manage own