Do you want to be a part of a dynamic research department focusing on making genetic discoveries for drug discovery? Do you want to join an exciting and newly established academic-industrial translational research institute in Oxford? Do you have experience in genomic research of cardiometabolic diseases? Then you might be the new Postdoc Scientist we are looking for.
About Novo Nordisk Research Centre Oxford (NNRCO)
NNRCO is our translational research institute focused on understanding biology and target discovery across the broad spectrum of cardiometabolic disease. We aim to combine the very best of academia, biotech and big pharma, fusing a deep understanding of human genetics, an agile, creative and collaborative culture with drug development. NNRCO will be a world-leading research site focused on asking the big and difficult questions and delivering high impact science. We will use human genetics, functional genomics, human-centric disease models and computational biology to develop an unparalleled understanding of cardiometabolic disease and deliver therapies that transform the lives of patients.
Our location in the heart of the University of Oxford medical campus enables two-way collaborations with some of the best medical scientists in the world. Our agile creative culture allows our scientists a high degree of individual autonomy to drive their own projects building on deep internal and external collaborations. Furthermore, cross-country collaborations within the organization are part of our normal working environment and NNRCO scientists are an integral part of the Novo Nordisk Global Drug Discovery unit.
You can read more about Novo Nordisk Research Centre Oxford at: www.novonordisk.com/research-and-development/science-and-innovation/global-r-and-d-centres/novo-nordisk-research-centre-oxford.html
The new Department of Genetics is led by Sr. Director, Joanna Howson PhD, and will consist of Specialists, Staff Scientists and Postdocs. The focus of this Department is to use data science and human genetics to enable discovery of new drug targets, this will be through a range of approaches e.g. high-throughput genetic discovery screens; evaluation of pLoF variants using in house data from across ancestries; Mendelian Randomization techniques and precision medicine approaches relevant to type 2 diabetes, non-alcoholic steatohepatitis (NASH) and cardiometabolic traits more broadly.
We are looking for a highly motivated Research Scientist in statistical genomics with a passion to work on state-of-the-art projects in human genetic-driven drug discovery for cardiometabolic diseases. The post-holder will work on a project that aims to identify the impact of the coding variants on human phenotypes and provide information for target validation and target discovery. In this position you will be responsible for developing and applying novel statistical models to analyze large-scale datasets, European and South Asian biobanks. The postdoc will work to develop and apply statistical methodology to create a framework that covers both single variant and gene-based (aggregate) tests for rare functional variants against cardiometabolic diseases. There is scope to apply machine learning algorithms and advanced computational tools to produce new biological insights into the results of GWAS in cardiometabolic disease
Finally, the project includes testing of hypotheses and analysis of data from a variety of sources, including a broad spectrum of OMICs datasets that Novo Nordisk has acquired or generated.
Applicants are asked to clearly indicate, in a cover letter, their motivation to work with human genetics in the early stages of the drug discovery process.
The position is temporary for 36 months.
22 October 2019
Working at Novo Nordisk
At Novo Nordisk, we use our skills, dedication and ambition to help people with diabetes and other chronic diseases. We offer the chance to be part of a truly global work place, where passion and engagement are met with opportunities for professional and personal development.
You have a PhD in a relevant field e.g. statistical genetics, software engineering or computational genetics teamed and a good understanding of human genetic data and genome-wide association studies (GWAS). Ideal candidates will have experience of coding analysis pipelines, analysing and evaluating ‘omics data such as transcriptomics/proteomics/metabolomics and integration of these data to elucidate causal genes and pathways. A good understanding of statistical concepts, 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 strong background in cardiometabolic trait research and machine learning would be an advantage.
The job requires proficiency in English and excellent communication and collaboration skills.
Click here to apply: onta.me/r/5d94adaaac26e