Research Assistant - £26,715 - £30,942
Research Associate* - £32,816 - £40,322
We are currently seeking a talented and highly motivated postdoctoral researcher in multi-omics and machine learning to join our team at the Health Data Research UK (HDRUK) Multi-omics Consortium, based at the Cambridge Department of Public Health and Primary Care (DPHPC). The post will suit an ambitious researcher, who is interested in applying their skills in machine learning, high-dimensional statistics, genomics, polygenic scores, and data integration.
The primary role of the post holder will be to lead projects involving the modelling, analysis and interpretation of genomic and multi-omic data as well as the development of new methodologies to integrate multi-omics datasets across HDRUK, including the Unit's vast portfolio of genomic, molecular, cellular and health data. They will also collaborate closely with Prof Christopher Yau (University of Manchester; https://cwcyau.github.io) on statistical and deep learning methods development.
The successful role-holder will have prepared research objectives consistent with the goals of HDRUK and 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 and 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. They would also have aspirations of developing a proposal for a competitive fellowship (e.g. Wellcome, MRC, BHF), thus leveraging this exciting emerging resource.
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.
- PhD in a quantitative field such as Statistics, Computer Science, Mathematics, Statistical Genetics, Bioinformatics, Biostatistics or have equivalent qualifications or equivalent experience
- In-depth knowledge of and demonstrated experience in machine learning or deep learning
- Knowledge of statistical genetics (e.g. GWAS, QTL analysis, polygenic risk scores)
- Strong quantitative analysis skills using statistical programming packages such as R
- Experience working with Linux and high performance computing
- Experience with programming and scripting languages (e.g. C, C++, Java, Python)
- Excellent communication and collaboration skills
- Working knowledge of proteomics, transcriptomics or metabolomics.
In addition to these skills, the post-holder should also be able to work independently judging priorities and have excellent organisational skills.
*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.
The funds for this post are available for 18 months start date 1 October 2020 ¿ 31 March 2022
The post-holder will be based at Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN (approx. 2 miles south of city centre)
Informal enquiries can be made to Prof Mike Inouye by email (email@example.com).
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Closing Date: 2nd November 2020
Interview Date: Week commencing 16th November 2020
Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please include details of your referees, including e-mail address and phone number, one of which must be your most recent line manager.
Please quote reference RH23371 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
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