Bioinformatics Doctoral Research Fellow: Methods development for functional assessment of impact of genome variation - Translational Bioinformatics
Prof W Hide
Prof N Lawrence
Applications accepted all year round
Competition Funded PhD Project (European/UK Students Only)
Project Details: 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.
The work will be in the Hide Laboratory at the Centre for Genome Translation https://hidelab.wordpress.com at the Sheffield Institute for Translational Neuroscience (SITraN) (http://sitran.dept.shef.ac.uk) a purpose built research facility which was opened in November 2010 by Her Majesty the Queen. The Institute houses computational, clinical and basic scientists with a focus on neurodegenerative disorders such as Motor Neurone Disease (MND) and Parkinson’s disease.
You will identify, develop and action methods that address functional variants that are thought to drive disease risk in 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. 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 to functional interpretation of genome variants and genome re-arrangements from large scale genome surveys. The student will be guided by Prof. Winston Hide (computational biology) and will have access to the mathematical expertise of collaborator Prof. Neil Lawrence, developing mathematically sound frameworks and methods.
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.
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
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
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.