Applying a Robot Scientist to Modelling Cancer Cells

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Funding

  • Competition Funded Project (European/UK Students Only)
This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. The funding is available to citizens of a number of European countries (including the UK). In most cases this will include all EU nationals. However full funding may not be available to all applicants and you should read the full department and project details for further information.

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Project description

Challenge: The fundamental problem in treating cancer is that we don???t understand enough about healthy and cancerous human cells to intervene rationally to kill cancerous cells but not healthy ones.

Background: Human cells are incredibly complex, tens of thousands of genes, proteins, and small molecules interact in complex temporal-spatial ways. The only way to disentangle and model these interactions, and hence treat cancer, is through hypothesis formation, and reproducible experimentation. However, progress is slow because of the limited number of qualified human scientists. A Robot Scientist is a physically implemented laboratory automation system that exploits techniques from the field of artificial intelligence (AI) to automatically execute cycles of scientific experimentation. I currently have a DARPA grant to adopt the laboratory automation part of the Robot Scientist Eve to work with human cancer cells, the aim is to test statements taken from the scientific literature.

Goals: The goal of the Ph.D. would be to use Eve to automatically: hypothesise improvements to models of cell signalling in healthy and cancerous cells, form experiments to test theses hypotheses, to execute these experiments, and decide whether the model should be changed. This ambitious goal is possible within a Ph.D. because: computational models of cell signalling exist, the wet biology/automation work in adapting Eve has been done, and a similar cycle of model improvement has been achieved in modelling yeast metabolism.

Possible outcomes: New AI techniques for automating scientific reasoning using robotics. New biomedical knowledge about healthy and cancerous human cells.

Skills: The students should have a background in AI with an interest in biology.

This project is eligible for The James Elson Studentship Award in Artificial Intelligence. The James Elson Studentship will provide an outstanding candidate with fees and an enhanced stipend to carry out a 3-year PhD research project relating to artificial intelligence. The School of Computer Science offers this prestigious PhD studentship for September 2017 entry, for students from the UK and EU who are eligible to pay 'Home' fees.

The deadline for applications for this studentship is Friday 17th March.

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