Postdoctoral Fellow – Birney Research (Novo Nordisk)

Postdoctoral Fellowships
Hinxton, UK

Digital health data promises to further our understanding of an individual’s disease risk and to discover determinants of differential outcomes. Such analyses are experiencing a boost in different countries by aggregating anonymised medical records of large parts of the population in secure trusted research environments. The Danish healthcare system is one of the leading countries for systematic electronic healthcare information.

Additionally, different cohorts, such as the UK Biobank, exist that have genomically profiled hundreds of thousands of individuals and characterised their health via diverse assays from MRI-scans to detailed blood counts in conjunction with linking to their medical records. Yet analysing these troves of data from millions of individuals easily overwhelms most research applications.

Your role

As part of this international NovoNordisk funded research project, we aim to analyse the electronic health records of 8 million Danes to model and quantify the influence of medical history, family history, genetics and lifestyle on future disease risk. We have developed machine learning methods to scale such analyses to data from millions of participants and quantify the influence of thousands of different past and current events. We plan to conduct these analysis across the entire catalogue of ICD-10 disease codes.

The resulting detailed risk assessments will be of unprecedented depth for each individual, will enable the identification of new risk factors and ultimately allow better schemes for disease prevention to be developed. Such analyses will also be replicated in the UK using resources provided by the UK Biobank and NHS digital. The work will be conducted in the research groups Ewan Birney (EMBL-EBI, Cambridge UK) and Moritz Gerstung (DKFZ, Heidelberg, Germany)

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Closing date: 15 June 2021

You have

A successful candidate will have a PhD in mathematics, statistics, physics, computer science or related computational discipline with a proven academic track record of data science applications. Essential skills include deep knowledge of statistical machine learning and proficiency in programming in python or related languages.

You might also have

Highly desirable would be familiarity with TensorFlow, Pytorch, JAX and numpyro.

The candidate should have a natural curiosity to apply their quantitative talent to questions related to human health and to work in a multidisciplinary research environment.

Why join us

Do something meaningful
At EMBL-EBI you can apply your talent and passion to accelerate science and tackle some of humankind's greatest challenges. EMBL-EBI is a worldwide leader in the storage, analysis and dissemination of large biological datasets. We provide the global research community with access to publicly available databases and tools which are crucial for the advancement of healthcare, food security, and biodiversity.

Join a culture of innovation
We are located on the Wellcome Genome Campus, alongside other prominent research and biotech organisations, and surrounded by beautiful Cambridgeshire countryside. This is a highly collaborative and inclusive community where our employees enjoy a relaxed atmosphere. We are committed to ensuring our employees feel valued, supported and empowered to reach their professional potential.

Enjoy lots of benefits:

For more details please see our employee benefits page


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