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Bioinformatics Doctoral Research Fellow: Functional assessment of impact of genome variation - Translational Bioinformatics

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  • Full or part time
    Prof Hide
    Prof Shaw
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

We invite applications for a PhD studentship in the Department of Neuroscience at the University of Sheffield School of Medicine in the Sheffield Institute for Translational Neuroscience. A stipend and home/EU fees for 3 years will be awarded to the successful candidate. Overseas applicants can apply but have to show the evidence that the difference between the overseas fees and home/EU fees can be covered by other funding.

Using in-house tools as well as developing novel integrative approaches, your goal will be to work closely with genome survey scientists to develop and apply robust methods for functional interpretation of genome variants and genome re-arrangements from large scale genome surveys. The project will combine the relationship between human genome variant data generated from genome sequencing and RNAseq data from ALS models of the disease in mice that have been mutated in a gene that is prevalent in the disease (SOD1G93a). The student will be guided by Prof. Winston Hide (computational biology) and Prof. Pam Shaw (ALS expertise) and will have access to the mathematical expertise of collaborator Prof. Neil Lawrence, developing mathematically sound frameworks and methods.

This project aims to identify gene and pathway targets through better understanding of the fundamental mechanisms of neurodegeneration. As each disease-associated gene and variant is identified, their mutual interaction gives insight into the biological pathways involved the aetiology of neurodegeneration. The ultimate aim is identification of molecules that can be used as biomarkers for diagnosis and as targets for the development of better, personalised treatment.

More information on research activities in Dr Hide’s group on translational genomics is at https://hidelab.wordpress.com and http://sitran.dept.shef.ac.uk

Working in a stimulating environment with close association with clinical and wet lab scientists, you will be generate testable translatable discoveries. You will be trained and travel to local and international meetings, and you will collaborate closely with the groups at Harvard.

The new lab at Sheffield works in close collaboration with Harvard School of Public Health, Harvard Stem Cell Institute and Biogen Idec in Cambridge, USA and Sheffield departments of Computer Sciences and Neuroscience as well as Sheffield Hallamshire Hospital. In addition we are active members in UK, EU and Global cohort consortia.

You have a high calibre Masters degree (or equivalent qualification) in computational biology, biomedical research, genomics, computer science, mathematics, biostatistics, systems biology or combination of these. You have a strong biological background, and are skilled in scripting with demonstrated understanding of working together with biomedical researchers and quantitative computational biologists. You are confident in aspects of data integration and are enthusiastic about construction and analysis of biological networks and/or data integration. Highly motivated, you wish to work in a stimulating, international, scientific environment. You have excellent interpersonal, written and oral communication skills and seek exposure to a diversity of scientific projects. This PhD will involve close interactions with biological and quantitative collaborators in academia and industry. Interested applicants should send a current curriculum vitae and research statement to Professor Hide by 18 March 2015

Funding Notes

This project is fully funded with home fees (UK/EU) and a stipend of £13,863 per annum for three years and a generous consumables budget to cover project costs.

How good is research at University of Sheffield in Allied Health Professions, Dentistry, Nursing and Pharmacy?
Biomedical science

FTE Category A staff submitted: 64.66

Research output data provided by the Research Excellence Framework (REF)

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