Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oxford
- ;
- University of Cambridge
- AALTO UNIVERSITY
- KINGS COLLEGE LONDON
- UNIVERSITY OF VIENNA
- Durham University
- Heriot Watt University
- City University London
- King's College London
- Loughborough University
- University of Glasgow
- University of Liverpool
- University of London
- ; Technical University of Denmark
- ; University of Cambridge
- DURHAM UNIVERSITY
- Imperial College London
- Medical Research Council
- Nottingham Trent University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of West London
- 12 more »
- « less
-
Field
-
sleep; performing anatomical tract tracing; analysing existing and new datasets using python and Matlab using advanced statistical methods such as machine learning; collaborating with other members
-
, learning and decision making, you will have strong quantitative and programming skills along with a track record of designing neuromodulation and neuroimaging studies in healthy participants, of using
-
small highly motivated inter-disciplinary team working towards a shared goal. You will be responsible for the design and testing of original machine-learning based algorithms and models for multi-modal
-
developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
-
first experiments of the future quantum-computer technology that is orders of magnitude more efficient than existing quantum processors. Join us in shaping the future! As a result of five ERC grants
-
have experience in code development and/or use of first principles methods (e.g. DFT) and/or machine learning methods, as well as experience in working with experiments and/or experimental collaborators
-
challenge. We seek a senior computational biologist to apply these extensive in-house datasets toward the development of novel, domain-tailored machine-learning models and analytical methods. You will explore
-
Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
-
discipline (eg Statistics, Machine Learning, Biostatistics, AI, Engineering) with experience of developing and applying new methods. You will be able to develop research projects, with publications in peer
-
. 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