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Research Assistant/Associate* - Statistical Genetics (Fixed Term)

University of Cambridge - Department of Public Health and Primary Care

Location: Cambridge
Salary: £26,715 - £40,322
Hours: Full Time, Part Time
Contract Type: Fixed-Term/Contract
Placed On: 19th May 2020
Closes: 17th June 2020
Job Ref: RH23114
 

Research Assistant - £26,715 - £30,942

Research Associate* - £32,816 - £40,322

We are currently seeking a researcher to join our team at the Cambridge Baker Systems Genomics Initiative, part of the Cardiovascular Epidemiology Unit (CEU) and Department of Public Health and Primary Care (DPHPC). The post will suit a highly-skilled individual. 

The Cambridge Baker Systems Genomics Initiative (CBSGI) is an international partnership between the DPHPC and the Baker Heart and Diabetes Institute (Melbourne, Australia). CBSGI conducts world-leading interdisciplinary research with a major focus on the development of statistical and machine learning approaches as well as the application of bespoke approaches to multi-omics data from studies of >100,000 participants, with the goal of improving the prediction and prevention of cardiometabolic, respiratory and related diseases. The Director of CBSGI is Associate Professor Inouye, a Principal Researcher in Systems Genomics at the University of Cambridge. The CEU (Director: Prof John Danesh) conducts world-leading interdisciplinary research with a major focus on the prediction and prevention of cardiovascular diseases. More information can be found at http://www.phpc.cam.ac.uk/ceu/ and http://www.inouyelab.org/

The role-holder will have prepared research objectives consistent with the goals of the Initiative and be ready to present these at interview for their own and joint research whilst on the project.  The research should be written up for presentation and the role holder may support the PI on preparing grant applications for ongoing research.  The Department runs an MPhil, research staff are encouraged to be involved in the delivery of the MPhil programmes.  The post-holder will be expected to work with the wider team in driving successful results to initiatives being run by the partnership. 

The post-holder will also be expected to evaluate and develop the statistical methods necessary to test hypotheses of interest, such as those listed above and advise on appropriate statistical practices. The work of the post-holder is expected to lead to first author high-impact publications.

Essential Qualifications/Skills

  • PhD in a quantitative field such as Statistical Genetics, Biostatistics, Bioinformatics, Systems Biology, Statistics, Computer Science, Mathematics or equivalent qualifications or equivalent experience
  • In-depth knowledge of and demonstrated experience in statistical genetics (e.g. GWAS, QTL analysis, polygenic risk scores)
  • Strong quantitative (in silico) analysis skills using statistical programming packages such as R.
  • Experience with programming and scripting languages (e.g. C, C++, Java, Python). Linux and high performance computing.
  • Excellent communication and collaboration skills. 

Desired Knowledge/Skills

  • Demonstrated statistical/computational methods development and software
  • Experience with proteomics, transcriptomics or metabolomics.
  • Working knowledge of electronic health records

*Appointment at research associate is dependent on having a PhD (or equivalent experience is recognised), including those who have submitted but not received their PhD. Where a PhD has yet to be awarded or submitted appointment will initially be made at research assistant and amended to research associate when the PhD is awarded.  If an individual has not submitted a PhD or is not working towards one they could be appointed as a Research Assistant if they have either a degree (degree and/or Master’s) in a relevant area or equivalent experience.  

Full time position. We will consider applications for part-time working of no less than 80% FTE per week.

Funds available for 2 years.

To apply online for this vacancy and to view further information about the role, please visit :

http://www.jobs.cam.ac.uk/job/25913.

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