Sort by
Refine Your Search
-
Listed
-
Employer
- ;
- University of Oxford
- KINGS COLLEGE LONDON
- Durham University
- University of Cambridge
- University of London
- King's College London
- Heriot Watt University
- University of Liverpool
- University of Glasgow
- DURHAM UNIVERSITY
- Nature Careers
- University of Birmingham
- University of Nottingham
- University of Sheffield
- ; Swansea University
- ; The University of Edinburgh
- ; University of Cambridge
- AALTO UNIVERSITY
- Aston University
- Imperial College London
- Oxford Brookes University
- St George's University of London
- Swansea University
- UNIVERSITY OF VIENNA
- 15 more »
- « less
-
Field
-
responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
-
responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
-
to target specific transcription factors (iii) use of high content imaging and AI to phenotype these cultures (iii) use of bulk and single-cell RNAseq to characterise the transcriptional profile of each cell
-
Professor Hing Leung and the wider multi-disciplinary research team. We are looking for candidates with experience/strong interests in learning some of the following: deep learning, medical imaging, and
-
frequency stabilisation and control, image analysis, data acquisition, optical design and Gaussian beam propagation. Desirable: 4. Experience · Demonstrable ability to develop research proposals
-
equivalent. B2 A knowledge of Raman microscopy and/or single cell Raman spectra analysis. Skills Essential: C1 Microfluidic techniques used to manipulate molecules or particles. C2 Instrumentation and imaging
-
detection, segmentation, classification, and pose estimation, as well as integrating these models into real-time systems. The role will involve working with large and multi-modal datasets (e.g., images, video
-
models of spillover infection and transmission of prototype viruses representing viral families concern to support the development of methods for virus sequence analysis and inference of human transmission