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Postdoctoral Fellow

Organization
EMBL-EBI
Job Location
Wellcome Genome Campus
Hinxton
CB10 1SD
United Kingdom
Salary
Year 1 Stipend (monthly stipend starting at £2,752.13 after tax).
Benefits

EMBL is an inclusive, equal opportunity employer offering attractive conditions and benefits appropriate to an international research organisation.

If you’ve ever visited the campus you’ll have experienced first-hand our friendly, collegial and supportive atmosphere, set in the beautiful Cambridgeshire countryside. Our staff also enjoy excellent sports facilities including a gym, a free shuttle bus, an on-site nursery, cafés and restaurant and a library.

Job Description

The European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI) is seeking a Postdoctoral Fellow to join the Gerstung research group, which works in the area of computational cancer biology.

Cancer is a disease driven by the life-long accumulation of mutations in our cell's genomes. The cancer data science group develops and applies statistical methods to large cancer data sets to gain insight into the origins of cancer and to implement models to predict cancer progression and outcomes. To achieve this, the group works with genomic, transcriptomic and imaging data sets from thousands to millions of cancer patients.

The Gerstung group has made several contributions to detect the first changes in cancer cells and predict the rates of developing cancer, based on these data. We have also developed genomic classification schemes that showed that the same cancers can often be subdivided into multiple genetically distinct groups and implemented personalised prognostic online calculators that yield a detailed risk assessment based on each patient's individual genetic makeup.Your roleAs a Postdoctoral Fellow in the group you will contribute to our research portfolio, ranging from cancer evolution and single cell analysis over imaging and spatial transcriptomics to large scale epidemiological data analysis projects.

You will drive your own research project, develop and apply a wide range of machine learning algorithms to gain deeper insights into the root causes of cancer. In doing so you will collaborate closely with other members of the group as well as local and international collaboration partners.

Requirements

You have

  • A doctoral degree or equivalent qualification in computational biology, genomics, statistics, computer science, physics or related field;
  • Previous experience with advanced statistical and machine learning tools such as R, Python, or Matlab and have an interest to apply these skills to improve our understanding of cancer;
  • A strong publication record;
  • The ability to drive and contribute to research projects and independently develop new research ideas;
  • Previous experience in coding and mastering large data volumes;
  • Excellent communication skills to clearly present your research ideas to experts as well as lay audiences.

You might also have

  • Experience with analysing genomic and other high-dimensional biomedical data sets
  • A background in molecular biology, or previous experience tackling biological questions;
  • Used and developed tools for interactive reporting, such as Shiny.
How to Apply

Applications are welcome from all nationalities and this will continue after Brexit. For more information please see our website. Visa information will be discussed in more depth with applicants selected for interview.

EMBL-EBI is committed to achieving gender balance and strongly encourages applications from women, who are currently under-represented at all levels. Appointment will be based on merit alone.

Informal enquiries can be directed to Dr Moritz Gerstung.

Applications will close at 23:00 British time on the date listed above.

About Our Organization

We have an informal culture, international working environment and excellent professional development opportunities but one of the really amazing things about us is the concentration of technical and scientific expertise – something you probably won’t find anywhere else.

At the Guardian, the University of Edinburgh's Nikolay Ogryzko argues that universities need to better invest in postdocs' careers.

Researchers who go persevere after an early funding setback end up with more highly cited papers later on, according to the Economist.

Nature News reports that female scientists setting up their first labs tend to have lower salaries and smaller staffs than their male peers.

A new analysis by Northwestern University researchers finds that female and male first-time PIs receive differing amounts of funding.