25 holidays plus public and bank holidays pro rata
over 1 year ago
In this position you will identify targets using human genetic, genomic and related data from in-house sources, external collaborations and data available publicly to achieve this goal. You will also work alongside other statistical geneticists, computational and laboratory scientists and with external collaborators to discover and validate new genetic findings and therapeutic targets.
This role will suit candidates who enjoy a fast-paced, dynamic environment where creative intellectual independence is actively encouraged.
You hold a PhD in statistical genetics, genetic epidemiology or related discipline, combined with an in-depth understanding of human genetic data, Mendelian Randomisation and genome-wide association studies (GWAS) particularly in relation to cardiometabolic traits.
Ideal candidates will have experience of analysing biobank sized data sets such as UK Biobank and exploiting 'omics data (e.g. metabolomics) to understand GWAS findings. A good understanding of statistical concepts, Mendelian Randomisation, experience of manipulating and managing large datasets and strong computational skills including in statistical packages e.g. python, R, perl, bash would be highly desirable. A proven track-record of developing successful collaborations would be an advantage.
You will be expected to work well both independently designing and driving the direction of projects, as well as collaboratively as part of a team alongside other inter-disciplinary colleagues in the project team, across departments and with external collaborators. You show a positive "can-do" attitude, are flexible, open to new ideas and are results oriented. The job requires proficiency in English and excellent communication and collaboration skills.
The position is temporary for 36 months.