Project Title: Machine learning-based automated hypothesis generation from microscopy images and their associated genome-wide metadata
Supervisor(s) names: Ilan Davis and Stephen Taylor
Department(s)/Organisation(s): Biochemistry, Whetherall Institute of Molecular Medicine, Oxford e-mail: ilan.Davis@bioch.ox.ac.uk and firstname.lastname@example.org
Tel: 01865 613265
Deadline: 13th July 2018
Brief description of project: (This project is supported through the Oxford Interdisciplinary Bioscience Doctoral Training Partnership (DTP) studentship programme. The student recruited to this project will join a cohort of students enrolled in the DTP’s interdisciplinary training programme, and will be able to take full advantage of the training and networking opportunities available through the DTP. For further details please visit www.biodtp.ox.ac.uk.)
The volume of microscopy images and their associated genome-wide metadata that are generated by many biologists is too large to be effectively browsed and interpreted in order to formulate novel testable hypotheses. Overcoming this challenge is of key importance for future biological discovery as data volumes continue to grow exponentially. The project will bridge this important technological gap in a unique partnership between a biomedical research lab lead by Prof. Ilan and Zegami (https://zegami.com), an Oxford University spinout company, whose founder and Chief Scientific Officer is Stephen Taylor. Zegami provides innovative cloud-based software to display vast databases of images sorted interactively in real time with complex metadata (example described in: https://www.youtube.com/watch?v=32bqn-Agt08). The main aim of the project is to develop machine learning software (using supervised random forest algorithms) that automatically generates scientific hypotheses based on correlations between existing high quality imaging data and genome-wide bioinformatics data, with guidance from the user. BBSRC REMIT AND FUNDING PORTFOLIO: “Tools and technology underpinning biological research”, specifically “data driven biology” and “exploiting new ways of working” and the area of artificial intelligence using supervised machine learning algorithms.
For informal queries about this exciting opportunity please contact Darragh (email@example.com).
We are always interested in hearing from prospective PhD/D Phil students. The lab is currently interested in a range of research areas, using Drosophila as a model, including mRNA localisation, regulation of synaptic plasticity, brain development and advanced imaging techniques. We are committed to training graduate students and foster them in the development of their own ideas. We welcome informal enquiries by email to: firstname.lastname@example.org . Please attach a CV and a short statement explaining your motivation to undertake a PhD.
Be aware that all prospective graduate students will have to formally apply to a competitive graduate studies program before they can join the the Davis Lab.
More information about the DPhil program in the Biochemistry department can be found here
We also host students from the following programs:
- Graduate training programme in Neuroscience
- Chromosome and Developmental Biology
- Interdisciplinary Bioscience Doctoral Training Partnership Programme (DTP)
There are currently no vacancies in the our lab. We do however welcome enquiries for researchers interested in applying for fellowships and other funding to email@example.com