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Machine learning of multi-omics data for better diagnosis and treatment of complex human disorders.

Project Description

We welcome applications for a PhD studentship available at the Dept of Computer Science, University of Sheffield in collaboration with the Sheffield Institute for Translational Neuroscience and the A*STAR Singapore Institute for Clinical Sciences. These two project mostly involve developing computational methodology for real-world applications in healthcare. While specific applications and approaches are mentioned, they can be tailored to the student’s personal interests.

Project (3.5 years in Sheffield with visits to Singapore):
The deluge of data from screening thousands of drugs and profiling thousands of genes have made machine learning a useful tool for predicting genetic associations to drug response. Several research teams, including ours, have recently tested a variety of machine learning approaches for predicting drug response in different cell lines using genomic data, however, prediction accuracy was low whenever predictions were attempted for new disease contexts due to limited number of samples, for example in rare diseases or complex diseases with many subtypes (Costello et al., 2014; Silverbush et al., 2017; Menden et al., 2019). By learning from the entire dose-response function and modelling uncertainty using Gaussian Processes, we can extend our existing strategies for predicting drug responses and improve on the transfer learning of drug response across different biological contexts. Simply, transfer learning focuses on storing knowledge from solving one problem in order to help solve a similar but different problem. Through this project we hope to provide proof of concept for transfer learning applied to drug response prediction from cancer to neurological disorders.

Required Qualifications:
A first-class or upper second class honours degree in Mathematics, Statistics, Physics, Computer Science or Engineering discipline.

If English is not your first language, you must have an IELTS score of 6.5 overall, with no less than 6.0 in each component.

To formally apply for the studentship, applicants need to apply directly to the University of Sheffield using the online application system. Please name Dennis Wang and Mauricio Alvarez as your proposed supervisors.

For more information on how to apply and a link to our application system, please see here:

Applications should include a personal statement, CV, transcripts and two references.

The personal statement (up to 4 A4 pages, including references) should outline your reasons for applying for this scholarship and how you would approach the researching, including details of your skills and experience in computational modelling and data analytics.

Funding Notes

Funding is eligible to UK/EU students only. Tuition fees are covered and a stipend will be provided at the RCUK rate of £15,285 / year in the UK. Expenses for Singapore visits will be covered as follows:

Living allowance: A monthly stipend of 2500 Singapore Dollars (~£1,050) whilst in Singapore
Housing allowance: Up to ~£300 per month.
A one-off "settling-in allowance" of 1000 Singapore dollars (~£420).
A one-time airfare allowance of 1500 Singapore dollars (~£630).
Conference allowance of £3000.
Consumables and Bench Fees incurred by students when based at A*Star in Singapore.
Cost of medical insurance whilst based at Singapore.

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