Vacancies
PhD studentship in Multimodal Representation Learning in Biological Data
Applications are invited for a PhD studentship in the field of Multimodal Representation Learning in Biological Data, which will be jointly hosted by Department of Electrical and Electronic Engineering and the College’s new I-X initiative. Home and Overseas applicants are eligible for this studentship. It is especially targeted at PhD applicants with an interest in artificial intelligence and medicine. Prospective students will also join the Biomedical Image Analysis Group.
The PhD research will explore the important topics of multimodal representation learning in biological data. Particularly, the research project will focus on finding the synergy between artificial intelligence (AI) and the large-scale multimodal high-content screening data. It will create innovative multimodal representation learning techniques that are beyond supervised learning, for realizing more efficient and accurate inference of biological relationships amongst genetic and chemical perturbations. The research is at the intersection of artificial intelligence and medicine and has the potential to make a widespread impact on the future of AI-enabled drug discovery and ultimately bring significant benefits to the pharmacy industry.
Qualification: Applicants are expected to have a First Class or Distinction Masters level degree, or equivalent, in a relevant scientific or technical discipline, such as computer science, mathematics or engineering. Applicants should also meet the minimum requirement as outlined in the guidance on qualifications. Applicants must be fluent in spoken and written English. Good team-working, observational and communication skills are essential. Experience in one or more of the following areas is desired: machine learning, deep learning, mathematical modelling, and software engineering.
How to apply: To Apply, please choose Electrical and Electronic Engineering Research Program and Intelligent Systems and Networks Group then indicate Dr Chen Qin as a potential supervisor when making the application.
Early applications are encouraged. The recruitment is on a rolling basis. The post is preferred for candidates who can start in January or April 2025. For further details of the post, please contact Dr Chen Qin at c.qin15@imperial.ac.uk. For queries regarding the application process, please contact eeepgadmissions@imperial.ac.uk.
If you are interested in the position, please feel free to get in touch with Dr Chen Qin - c.qin15@imperial.ac.uk:
- A full CV, with a list of all publications
- A short statement indicating what you see are interesting research issues relating to the above post and why your expertise is relevant.
- Any element relating your experience / passion for software engineering (blog, open source projects, GitHub repositories, and others) will be carefully inspected.