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Postdoc Fellow - Predicting High-Affinity Antibody Producing B-Cells

Местоположение Кембридж, Англия, Великобритания Идентификатор вакансии R-099332 Дата публикации 02/01/2021

Competitive Salary on Offer

Based in Cambridge, England

About the Program:

We’re currently looking for talented scientists to join our innovative academic-style Postdoc. From our centre in Cambridge, UK, you’ll be in a global pharmaceutical environment, contributing to live projects right from the start. You’ll join a company focused on drug discovery and development, be given access to our existing Postdoctoral research, and encouraged to pursue your own independent research in cutting edge laboratories. It’s a newly expanding programme spanning a range of therapeutic areas across a wide range of disciplines.

What’s more, you’ll have the support of a leading academic advisor, who’ll provide you with the guidance and knowledge you need to develop your career. This is an exciting area that hasn’t been explored to its full potential, making this an opportunity to make a real difference to the future of medical science.

About the Opportunity:

Do you want to play a key role furthering important scientific research at AstraZeneca? Here’s your chance.

Utilising cutting-edge technologies, such as single B-cell RNA sequencing combined with in silico molecular modelling of antigen:antibody interactions, this project aims to understand how to drive immune responses to produce better antigen specific antibodies. If this is your passion, don’t miss out on this role.

A detailed understanding of the process of B-cell affinity maturation has been hindered by the inability to track the behaviour of individual B-cells upon interaction with antigens. For this post-doctoral project, we hypothesise that the process of affinity maturation is echoed in the B-cell transcriptomic profile, and, therefore, we aim to investigate this through single B-cell RNA sequence analysis of both the B-cell receptor repertoire and the B-cell transcriptome. This data will be combined with in silico modelling of antigen:antibody interactions in order to generate a better understanding of the B-cell affinity maturation process to enable us to generate higher affinity target specific antibodies . This project has the scope to influence multiples areas of knowledge ranging from the  better understanding of how higher affinity antibodies are generated to cope with pathogens to having a better insight of  how B cell autoimmune diseases occur. 

The postdoc will be embedded in a highly interactive team of bench biologists and data scientists. The postdoc position will enable learning data science skills, expanding their single cell analysis abilities and extending the possibility to interact with protein-protein interaction data scientists from AZ. And, the Postdoc will collaborate with scientists from a variety of functional teams in Cambridge and with our site in Gaithersburg, USA

Education and Experience Requirements:

  • PhD in relevant discipline
  • Technical expertise in bioinformatics, computational biology, biostatistics, data science with special focus on single cell data analysis
  • Proficient with programming languages such as Python, R or Perl.
  • Demonstrated ability to work independently & effectively collaborate with others
  • Enthusiastic to explore non-traditional approaches to bring big data together in biologically meaningful ways.
  • Strong written and oral communication skills, able to effectively present data and demonstrate critical analyses of data sets, including to non-experts.

Desirable Qualifications:

  • Understanding basic immunology, familiarity with antibody VDJ sequence analysis and utilisation of relevant bioinformatic tools to achieve this.
  • Experience of software packages for in silico modelling of protein:protein interactions (e.g. Rosetta suite etc.)
  • Excellent publication record
  • Well networked within external bioinformatics communities.
  • Effective contributor to collaborative projects involving cross-disciplinary/ global teams.
  • Awareness of graph modelling, machine learning, artificial-intelligence

Skills and Capabilities required:

  • Lead single cell analysis and interpret transcriptomic expression (desirable other single cell-omics data)
  • Design and apply innovative computational/statistical algorithms and visualizations to:
    • Generate biological insight from omics data.
    • Integrate and interpret proprietary and public data.
  • Collaborate with other single cell Omics groups in AstraZeneca, within industry and academia, and utilise external resources to find the most effective solutions.
  • Highly organized and self-motivated, with the ability to work well as part of a team

Why AstraZeneca?

At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration, and always committed to lifelong learning, growth and development. We’re on an exciting journey to pioneer the future of healthcare.

This is a 3-year programme. 2 years will be a Fixed Term Contract, with a 1 year extension which will be merit based. The role will be based in Cambridge, UK, with a competitive salary on offer

Advert opening date – Feb 1, 2021

Advert closing date – May 2 , 2021

So, what’s next?

  • Are you already imagining yourself joining our team? Good, because we can’t wait to hear from you.

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.

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