Project Description

At Leicester we’re going places. As a leading University in Britain our aim is to climb further. A commitment to high quality fused with an inclusive academic culture is our hallmark and led the Times Higher Education to describe us as “elite without being elitist”.

In this position you will support association analyses for large scale datasets. These could include genome-wide association studies or resequencing studies, or risk modelling for verified discoveries, with a particular focus on cardiovascular and respiratory traits.

You will also undertake independent research that contributes to new intellectual understanding, under direct supervision and guidance.

You will have a degree level qualification in a relevant discipline and have experience or, at least, basic knowledge of epidemiological study design and data analysis. You will also have good knowledge of R statistical software

Job Purpose:

To support association analyses for large scale datasets. These could include genome-wide association studies or resequencing studies, or risk modelling for verified discoveries, with a particular focus on cardiovascular and respiratory traits; To undertake independent research that contributes to new intellectual understanding, under direct supervision and guidance.

Principal Accountabilities:

Support the research team through the appropriate data management, data cleaning, analyses and interpretation of the research data.

  • Be responsible for the maintenance and version control of the relevant data.
  • Prepare and undertake analyses and tests using techniques and approaches agreed by the line manager.
  • Identify and understand work requirements prioritising tasks and responsibilities within an agreed timeframe agreed with the line manager.
  • Contribute to the development of new statistical approaches of relevance.
  • Undertake literature searches relevant to developing new projects or to placing new research findings into context.
  • Work within the agreed protocols defined by the research team and University computer policy.
  • Document the research findings, assessing the outcomes and options emerging from the research.
  • Contribute as a junior partner to the writing and publication of project reports, presentations and research papers.

Work closely with investigators and collaborators. Includes regular meetings with team members, between investigators (teleconferences/videoconferences and face-to-face meetings) and occasional attendance at national or international meetings where relevant.

Develop new knowledge relating to statistical analyses of genetic association studies and maintain up-to-date knowledge required to interface effectively with other researchers in the program.

Qualifications, Knowledge and Experience:

Essential
  • Possess a degree level qualification in a relevant discipline
  • Experience or, at least, basic knowledge of epidemiological study design and data analysis
  • Good knowledge of R statistical software
  • Sound programming skills in R or an alternative software for statistical analysis
Desirable
  • MSc in a relevant discipline (or the equivalent in professional qualifications and experience) Experience of statistical genetics or genetic epidemiology is not necessary (as training can be provided), but a willingness to learn new approaches is essential.
  • Excellent computer programming skills
  • Practical experience in medical statistics or a related field
  • Experience of statistical genetic analyses and basic knowledge of human genetics
  • Experience of bioinformatics
  • A working knowledge of UNIX as well as Windows operating systems

Skills, Abilities and Competencies:

Essential
  • High level of proficiency in English, sufficient to undertake research, teaching and administrative activities utilising English Language materials and to communicate effectively with staff and students
  • Sound statistical skills
  • Excellent written communication skills*
  • Excellent verbal communication skills
  • Ability to work independently and also as part of a research team.
Desirable
  • Excellent time management skills