PhD Studentship: Deep Learning for Large-Scale Analysis of Brightfield and Multiplexed Whole Slide Images.

We are seeking a PhD student in deep learning (DL) and artificial intelligence (AI) to research and develop tools and methods for the large-scale analysis of multiplexed digital multi-gigapixel whole-slide images of cancerous tissue sections. The project aims to develop tissue/organ-agnostic DL models for registration, detection, segmentation and classification of a broad range of tissues using brightfield and multiplexed imaging. You will develop explainable AI methods for correlating the histological signatures with genomic alterations, treatment response and clinical outcome.

This is an immensely exciting opportunity to join the HistoMaps (HistoMaps: Stain agnostic feature representations to identify clinically relevant traits in the tumour microenvironment) project team based in the Department of Computer Science, University of Warwick as a PhD student. The collaborative project is led by Tissue Image Analytics (TIA) Centre at the University of Warwick and provides an exciting opportunity to join a multidisciplinary dynamic team with collaborators from Warwick Medical School, University Hospitals Coventry and Warwickshire, University College London, Institute of Cancer Research, Royal Marsden Hospital and Nvidia on the MONAI project.

You will be involved in the development of tools which allow creation of unified HistoMaps using a combination of widely used HE or immunostained (IHC/MxIF) images and link feature representations from HistoMaps to clinical variables. You will further participate in the deployment of these algorithms in the TIAToolbox (https://github.com/TissueImageAnalytics/tiatoolbox).

This is an exciting opportunity to join a dynamic team based in the Tissue Image Analytics (TIA) Centre, Department of Computer Science, University of Warwick. The TIA Centre at Warwick is a global leader in computational pathology and focusses on developing AI algorithms for the analysis of digital pathology images for cancer diagnosis, grading and predicting cancer outcome. The computer science department at Warwick is one of the top-ranked computer science departments in the UK and offers excellent opportunities for research students to work on inter-disciplinary projects and develop a successful research profile.

Candidates should ideally have a computer science, engineering or data science background, although candidates from other scientific disciplines will be considered. Candidates should have strong analytical skills and should have solid programming experience in python, including developing or applying machine learning techniques (ideally using TensorFlow or PyTorch).

Supervisor(s): Dr Shan Raza, Tissue Image Analytics (TIA) Centre, Department of Computer Science, University of Warwick, UK.

For further details, please contact Dr Shan Raza on Shan.Raza@warwick.ac.uk

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