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Postdoctoral Fellow - ProID Project - Goldman Research



Job Location

EMBL-EBI, Wellcome Genome Campus, Hinxton
CB10 1SD
United Kingdom


Year 1 Stipend - £2,869.24 per month after tax


Enjoy lots of benefits:

  • Financial incentives: Monthly family, child and non-resident allowances, annual salary review, pension scheme including 17% employer contribution, death benefit, long-term care, accident-at-work and unemployment insurances
  • Flexible working arrangements
  • Private medical insurance for you and your immediate family (including all prescriptions and generous dental & optical cover)
  • Generous time off: 30 days annual leave per year, in addition to eight bank holidays
  • Relocation package including installation grant (if required)
  • Campus life: Free shuttle bus to and from work, on-site library, subsidised on-site gym and cafeteria, casual dress code, extensive sports and social club activities (on campus and remotely)
  • Family benefits: On-site nursery, child sick leave, generous parental leave, holiday clubs on campus and monthly family and child allowances

Job Description

We are looking for a postdoctoral-level scientist to join a new international collaborative project, “ProID”, funded by the European Commission, to create a proof-of-principle, high-throughput nanopore device for determining the amino acid sequence of proteins and protein fragments.

This is an exciting opportunity to join one of 18 research groups at EMBL-EBI totalling approx. 150 research scientists including approx. 45 postdocs.

You will work in the Goldman Group which researches novel genome and protein data analysis methods. Our contributions in the past include multiple sequence alignment methods; evolutionary analyses including methods for detecting natural selection; algorithms for Next Generation Sequencing basecalling; methods for optimal use of nanopore sequencers; and the creation of the field of DNA-storage, the use of DNA as a high-throughput digital information storage medium.

Your role

The ProID project element based at EMBL-EBI covers the bioinformatics aspects of the nanopore amino acid sequencer. You will have the key role in developing new methods to perform all the data processing tasks, from analysis of Raman spectroscopy-derived light spectra derived from amino acids translocating through nanopores through to identification of those amino acids and the proteins they comprise.

Success in this role will see you becoming an expert in nanopore sequencing bioinformatics, including the new possibilities for protein identification and sequencing.

As part of the role, you will have the opportunity to:

  • Build positive relations with international collaborators and experimental partners;
  • Apply your knowledge on mathematical models, statistical analyses and algorithmic implementations to perform computational molecular sequence analyses;
  • Be part of a highly collaborative network of scientists through EMBL’s Postdoctoral Fellowship programme: receiving dedicated career support, mentoring and have access to a variety of training opportunities.


You have

  • A PhD in computational biology, bioinformatics, or other scientific area incorporating significant molecular sequence analyses, or experience working at an equivalent level. 
  • Experience of:
    • performing a variety of computational molecular sequence analyses, and an understanding of the underlying mathematical models, statistical analyses and algorithmic implementations;
    • coding both complex pipelines, and individual numerical data processing steps, in well-known languages (likely Python, C or C++ for the numerical elements).
  • Ability to:    
    • perform scientific research at a postdoctoral level;
    • write technical documents and scientific papers in English;
    • work independently for some project elements, and collaboratively and in response to other project partners’ needs at other times.

You might also have

The successful candidate will likely have:

  • An understanding of mathematical model-based probabilistic analyses and/or machine learning techniques — ideally applied to molecular sequences. Experience in the design of novel algorithms and data analyses will be an advantage.  
  • Experience using a wider variety of computing languages.

How to Apply

To view a copy of the full job description please click here

  • Contract duration: This position is a 3 year fixed-term contract (estimated 01/11/2021-31/10/2024).
  • International applicants: We recruit internationally and successful candidates are offered visa exemptions. Read more on our page for international applicants.
  • Diversity and inclusion: At EMBL-EBI, we strongly believe that inclusive and diverse teams benefit from higher levels of innovation and creative thought. We encourage applications from women, LGBTQ+ and individuals from all nationalities.
  • Job location: This role is based in Hinxton, UK and you will be required to relocate once it is safe to do so, if you are currently based abroad. Read more about how we are recruiting during the pandemic.
  • Your application: To apply please submit a cover letter and a CV through our online system. We aim to provide a response within two weeks after the closing date: 24th August 2021. 

Job No.: EBI01880

About Our Organization

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.


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