Research Associate in Statistical Genetics and Bioinformatics

Job ID: 1671499
Job date: 2017-09-18
End Date:

Company : University College London 

Country :

Role : Research Scientist 


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Job Description:
We are recruiting a talented statistical geneticist/bioinformatician to determine the genetic basis of complex phenotypes in rice and chickpea, with the aim of improving these important crops. The methodologies developed by the project will apply to many crops and animals.

The post is funded by the UK Global Challenges Research Fund and the BBSRC.The post-holder will join the group of Richard Mott in the Genetics Institute (UGI) University College London (UCL), and will work in close collaboration with the International Rice Research Institute (IRRI), Philippines, and the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), India, and the National Institute for Agricultural Botany (NIAB), Cambridge. The postholder will join a dynamic team of statistical geneticists working on a variety of problems.

The project focuses on (i) the imputation of genome sequence from crop populations sequenced at low coverage, adapting methods developed previously in the group (e.g. Davies et al Nature Genetics 2015) (ii) the use of low-coverage population sequence to identify structural variants implicated in phenotypes (Imprialou et al Genetics 2017) (iii) The development and implementation of quantitative genetics and genomic prediction methods in crop development, particularly in relation to multiparental advanced intercrosses. (iv) Close collaboration, support and knowledge exchange with partner laboratories. The project will involve visits to both IRRI and ICRISAT.

The post is available from now until 30 June 2021 with possibility of extension.

PhD in Statistical Genetics, Bioinformatics or a related field is essential as is a good understanding of the statistics of genetic association and experience of manipulating and analysing Next-Gen sequence data. It is essential candidates demonstrate programming fluency in R, Perl/Python, or C/C++. The successful candidate must have experience of conducting research in statistical genetics or bioinformatics.

Full details on the role and the person specification can be accessed at the bottom of this page. Please ensure you read these carefully before applying for the post as candidates must meet all essential criteria to be considered.


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Additional Info:
To apply for the vacancy please click on the ‘Apply Now’ button. If you would like to discuss the post please contact Professor Richard Mott, r.mott@ucl.ac.uk For any queries regarding the application process, please contact Biosciences Staffing on biosciences.staffing@ucl.ac.uk and quote the reference 1671499.

Latest time for the submission of applications: 23:59.

Interview Date: tbc

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