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 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, have solid programming experience in python, including developing or applying machine learning techniques (ideally using TensorFlow or PyTorch) and hold a degree equivalent to a UK 2.1 minimum.

Supervisors: Dr Shan Raza, Prof Nasir Rajpoot, Tissue Image Analytics (TIA) Centre, Department of Computer Science, University of Warwick, UK.

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

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