Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- ;
- University of Oxford
- KINGS COLLEGE LONDON
- AALTO UNIVERSITY
- Imperial College London
- Nature Careers
- University of Birmingham
- University of Cambridge
- King's College London
- Heriot Watt University
- UNIVERSITY OF SOUTHAMPTON
- University of Nottingham
- University of Sheffield
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- UNIVERSITY OF SURREY
- UNIVERSITY OF VIENNA
- University of Cambridge;
- University of London
- University of Manchester
- The University of Southampton
- University of Glasgow
- University of Newcastle
- Durham University
- Medical Research Council
- Nottingham Trent University
- QUEENS UNIVERSITY BELFAST
- Technical University of Denmark
- University of Bath
- University of Bristol
- University of Leeds;
- University of Lincoln
- University of Liverpool
- ; Technical University of Denmark
- ; The University of Edinburgh
- ; University of Oxford
- Aston University
- Birmingham City University
- CRANFIELD UNIVERSITY
- City University London
- King's College London;
- Lancaster University
- Lancaster University;
- Nanyang Technological University
- Northumbria University;
- Plymouth University
- Queen's University Belfast
- Queen's University Belfast;
- Swansea University
- UCL;
- UNIVERSITY OF MELBOURNE
- Ulster University;
- University of Leeds
- University of Plymouth;
- University of Reading
- University of Surrey
- University of Surrey;
- University of West London
- 47 more »
- « less
-
Field
-
to science. This is the first large-scale study of its kind, and your results will establish a legacy of scientists working with funding councils to defend their research. Cutting-edge machine learning
-
annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
-
lab integrates machine learning and high-throughput biochemistry to study how proteins selectively recognise their substrates, how this process is perturbed in cancer and how it can be hijacked to find
-
qualification/experience in a related field of study. The successful applicant will have expertise in statistical modelling, epidemiology or machine learning and possess sufficient specialist knowledge in
-
should have experience of working with computational and analytical techniques in the areas of natural language processing (including, among others, topic modelling), computational linguistics, and machine
-
. Ready to be part of our team? Let’s shape the future together! About the team: The Computational Materials Discovery group is looking for a postdoctoral researcher working in the field of machine learning
-
ERC-funded postdoctoral fellow in theoretical developmental biology, using tools from applied mathematics, biophysics, and machine learning A talented and creative researcher is sought to take part
-
desirable, good quantitative training (e.g. undergraduate maths courses) is essential. Familiarity with and interest in machine learning approaches applied to biological problems is also desirable. Lab and
-
desirable, good quantitative training (e.g. undergraduate maths courses) is essential. Familiarity with and interest in machine learning approaches applied to biological problems is also desirable. Lab and
-
systems; 5G and beyond mobile networks, including Open RAN; Machine learning for networks and systems; Systems for machine learning; Edge computing and applications; Networked systems design and