Biomedical Statistician, University of Leicester

College of Medicine, Biological Sciences and Psychology

Department of Cardiovascular Sciences

Either

Salary Grade 6 - £25,504 to £29,541 per annum

or

Salary Grade 7 - £31,331 to £36,298 per annum

Open Ended Contract, subject to Fixed Term Funding. Funding is currently available till end of March 2015.


Ref: MBP00880

Applications are invited for the post of Biomedical Statistician in the Department of Cardiovascular Sciences. This post is funded by the EU-funded project “BIOSTAT-CHF” and available till 31st March 2015.

The primary role of the post holder will be to provide statistical advice and support in analysing data from large-scale human genetic studies of cardiovascular disease.

The post is particularly suitable for an individual who is interested in developing a career in applying statistical approaches to genomic and other large-scale “omics” data. The post-holder will join a Department at the forefront internationally of research into the genetics of cardiovascular diseases.

The post will be based in the British Heart Foundation Cardiovascular Research Centre at Glenfield Hospital. The post-holder will join team of two other statisticians and a large group of basic and clinical researchers. The post-holder will be jointly supervised by Professor NJ Samani (British Heart Foundation Professor of Cardiology and Head of Department) and Professor John Thompson, Professor of Statistics (Health Sciences).

The successful applicant will be appointed at either Grade 6 or Grade 7 depending on their experience, skills and qualifications.

BIOSTAT-CHF

BIOSTAT-CHF is a European Union Framework 7 Programme involving multiple centres across Europe, whose aim is to use a systems medicine approach to understand the determinants of poor prognosis in heart failure. Heart failure is a common condition affecting over 1 million people in the UK alone. Despite advances over the last 30 years in treating heart failure, it carries a bad prognosis with almost 50% of individuals diagnosed with heart failure dying within 5 years. The aim of BIOSTAT-CHF is to identify biological factors responsible for adverse outcomes despite best treatment. The project plans to integrate genomic, proteomic and clinical data to identify adverse risk factors. To this end the project has recently completed recruitment of 2,500 patients with heart failure who are being followed-up. DNA has been isolated from all patients and is currently undergoing genome-wide array-based SNP typing. Separately, plasma samples are being analysed for proteomic profiles using mass spectrometry. A separate cohort of 2500 patients has been assembled for replication of finings.

Your Role

Your primary role is to provide expert input into assembling, quality-checking and analysing the genome-wide array and other genetic data in BIOSTAT-CHF in relation to patient outcome. You will also play a key role in integrating and analysing the genetic data with respect to other data (e.g. proteomics) and contributing to the systems medicine analysis. This work will involve working extensively with national and international collaborators.

Working alongside the other statisticians in the Department, you will also be involved in broader research activities within the Department providing statistical input into other genetic and non-genetic projects, advising and training other members of staff and students in statistical methodology and in the preparation of research grants and scientific papers for publication. You will participate in and contribute to meetings of Professor Samani’s research group and attend other research activities in the Department (e.g. seminar programme).

You will be encouraged to seek out and attend courses and meetings that will help in your continual professional development and benefit your work in the Department.

You will report regularly to Professor Samani about progress with your research and discuss findings and prepare reports as necessary. Professor Thompson will provide guidance and mentorship on statistical aspects.

Please look at “Samani NJ” on PubMed to see the type of research outputs from the group

Principal Accountabilities

·         To conduct statistical analysis of the data from genetic experiments including large-scale genome-wide association studies

·         To liaise, as necessary, with other research partners in the University, UK and internationally and to participate in statistical aspects of any collaborative research

·         To prepare appropriate reports of any analysis and provide statistical input for preparation of peer-reviewed publications

·         To provide teaching, training and advice to members of the research team on selection of optimal statistical methodologies and appropriate interpretation of results

·         The post-holder will also be expected to:

o   To engage in relevant professional activities, including self-initiated learning of any relevant statistical platforms and engage in continuous professional development to widen areas of expertise

o   To participate in research activities including attendance of Departmental seminar programs, and relevant seminars as agreed with the PI

Additional responsibilities at Grade 7

·         To liaise, as necessary, with other research partners in the University, UK and internationally and to lead in statistical aspects of any collaborative research

·         To provide an increased proportion of teaching, training and advice to members of the research team on selection of optimal statistical methodologies and appropriate interpretation of results

·         To develop some independent lines of research to maximise the outputs from the data



Qualifications, Knowledge and Experience

Essential

·         Good first degree in a relevant discipline such as mathematics or biological science *

·         Higher degree in biostatistics, medical statistics or applied statistics (or a minimum of three years experience working as a statistician in a relevant setting)*.
Additional for Grade 7

·         PhD in Biostatistics, medical physics or applied statistics

Desirable

·         Prior experience of analysis of genetic research and/or knowledge of relevant genetic analysis platforms*

Additional for Grade 7

·         Evidence of research productivity (e.g. research publications in peer review journals, presentations etc)



Skills, Abilities and Competencies

Essential

·         Ability to undertake analysis using a range of quantitative statistical methodologies*

·         Good knowledge of R/STATA and other relevant statistical software*

·         Evidence of sourcing and adapting relevant statistical approaches to address specific needs of research projects*

·         Excellent verbal, written and presentation skills
Additional for Grade 7

·         Evidence of independence in research and more experience in selection of optimal statistical methodologies*

Desirable

·         Experience/evidence of involvement in statistical analysis of biological/genetic research*

·         Some experience with use of relevant bioinformatic resources – e.g. HapMap

·         Understanding of research structures and ethical review processes

 (* Criteria to be used in shortlisting candidates for interview)



Informal enquiries are welcome and should be made to Professor Nilesh Samani on [log in to unmask] or 0116 2044758


Applications

For further information and to apply on-line, please visit our website: www.le.ac.uk/joinus [Ref: MBP00880]

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