Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- ;
- University of Oxford
- Imperial College London
- KINGS COLLEGE LONDON
- University of Birmingham
- AALTO UNIVERSITY
- King's College London
- Nature Careers
- University of London
- University of Cambridge
- Heriot Watt University
- UNIVERSITY OF SOUTHAMPTON
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Nottingham
- UNIVERSITY OF VIENNA
- University of Manchester
- ; University of Oxford
- CRANFIELD UNIVERSITY
- Durham University
- QUEENS UNIVERSITY BELFAST
- Queen's University Belfast
- Royal College of Art
- The University of Southampton
- University of Glasgow
- University of Liverpool
- University of Newcastle
- University of Sheffield
- ; University of Kent
- ; University of Southern Denmark
- Birmingham City University
- City University London
- Manchester Metropolitan University
- Medical Research Council
- Nottingham Trent University
- THE HONG KONG POLYTECHNIC UNIVERSITY
- UNIVERSITY OF MELBOURNE
- UNIVERSITY OF SURREY
- University of Bristol
- University of Leeds
- University of Lincoln
- University of Reading
- University of Surrey
- University of West London
- 33 more »
- « less
-
Field
-
skills and experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation models Experience with Pytorch, MONAI, CUDA or equivalent software
-
modelling, satellite data assimilation, multivariate statistics, and machine learning. Prior experience with model and satellite products for mapping and understanding SM-dependent hazards (like floods
-
Applicants are invited for the posts of Research Associate or Research Fellow in Machine Learning to work with AI Researchers in the Centre for AI Fundamentals at the University of Manchester. You
-
: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A
-
Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
illnesses. The post holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning
-
, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded methodology project
-
to undertake world-leading research in the design, integration and Edge-implementation/testing of multimodal machine learning models. Your experience in real-time implementation of federated AI and Edge-based
-
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
-
computational analyses of epigenomic/transcriptomic data and machine learning. Experience in single-cell omics data is desirable. The post holder will be responsible to develop pipelines for the analysis
-
this suits a candidate with a background in optical systems / imaging, or with more experience in machine vision, or systems control and automation, or data interpretation. A candidate would not be expected