Sort by
Refine Your Search
-
Listed
-
Employer
- AALTO UNIVERSITY
- University of Cambridge;
- University of Cambridge
- University of Newcastle
- University of Nottingham
- ;
- KINGS COLLEGE LONDON
- NORTHUMBRIA UNIVERSITY
- University of Glasgow
- University of Oxford
- ; University of Cambridge
- Durham University
- Heriot Watt University
- King's College London
- Newcastle University;
- THE HONG KONG POLYTECHNIC UNIVERSITY
- UNIVERSITY OF MELBOURNE
- University of London
- University of Sheffield
- University of Sheffield;
- University of Strathclyde;
- 11 more »
- « less
-
Field
-
We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
-
machine learning. The position will involve working with different research groups in the Department of Computer Science at the University of Cambridge, UK. In this collaborative project, we will apply
-
28 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position
-
28 Aug 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Computer science Physics Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country
-
Meier and the wider Systems Science in Public Health team within the Public Health Unit, School of Health and Wellbeing. HealthMod is a large UK-wide research programme which connects scientists
-
: Functional genomics and psychiatric epidemiology Clinical informatics and data harmonisation Co-production and participatory research methods Working within a cutting-edge UK-wide data infrastructure
-
: Essential criteria MSc. in Neuroscience, Physics, Computer Science, or a related field Strong background in computational neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and
-
the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
-
applicant must have (or be close to obtaining) a relevant PhD in Fluid Mechanics from an Engineering, Mathematics or Physics Department, a strong background in theoretical and computational fluid mechanics
-
University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems