Associate Principal Scientist, Bioinformatics
Associate Principal Scientist, Bioinformatics
Waltham, MA or Gaithersburg, MD
At AstraZeneca we work together across global boundaries to make an impact and find answers to challenges. We do this with the upmost integrity even in the most difficult situations because we are committed to doing the right thing. We continuously forge partnerships that help pursue world-class medicines in new ways, combining our people’s exceptional skills with those of people from all over the globe. As an Associate Principal Scientist, Bioinformatics, Oncology you’ll play a pivotal role in channeling our scientific capabilities to make a positive impact on changing patients’ lives. We are focused on scientific advances in small molecules, oligonucleotides and other emerging technologies and drug discovery platforms.
Main Duties and Responsibilities
There is an exciting opportunity for a talented and motivated bioinformatician or biostatistician, eager to bring biological data together in new ways, to join the group as an APS. In this role, you will focus on development and application of approaches combining multi-omic data sets (including next-generation-sequencing) with phenotypic annotation to reveal actionable insights surrounding complex biological problems. You will work closely with bioscience and translational science teams to understand where bioinformatics approaches can best impact their scientific and technical challenges.
You will be responsible in steering the application of bioinformatics/genomics to benefit immuno-oncology drug projects. You will also design and apply innovative computational/statistical algorithms and visualizations to: Generate actionable biological insight from genomic data; Discover and develop new molecular target, mechanism and biomarker hypotheses for drug projects; Link multi-omic data sets from patients and in vitro/vivo models; Integrate and interpret proprietary and public data spanning multiple platforms. You will also be responsible to find new ways of interpreting, modelling or finding meaningful patterns in complex data. You will proactively engage in knowledge sharing and peer support, including training our bench science community, to build expertise in the tools critical to Oncology Bioinformatics. You will build and steer further development of small prototype tools for bench scientists to access and visualize project data. Finally, you will collaborate with industry and academia, and exploit external resources, to find the most effective solutions to problems.
- Relevant PhD; graduate degree plus a minimum of 5 years’ relevant experience can also be considered
- Minimum of one year post-doctoral or applied experience with combining technical expertise in either:
- genetics/genomics, oncology/immunology and computational biology
- biostatistics, mathematical modeling and human disease
- An enthusiasm to explore non-traditional approaches to bring big data together in biologically meaningful ways.
- Understanding of the biological systems and signaling involved in human disease.
- Programming in a Unix and Windows environment.
- R programming expertise (inc. use of Bioconductor and Shiny).
- Skilled in effective communication of complex data to a non-expert.
- Valuable contributions to scientific projects recognized through peer reviewed publication.
- Background which includes one of the following:
- Deep understanding of the molecular drivers of immunology and/or cancer; plus proficiency analyzing and interpreting data from multiple ‘omic platforms (NGS sequencing, transcriptomic, proteomic etc.).
- Expertise applying mathematical approaches to identify and interpret associations in diverse molecular and phenotypic data; knowledge of large-scale machine learning techniques.
- An excellent publication track record.
- Well networked within external bioinformatics and oncology communities.
- A thorough understanding of the contribution of bioinformatics to drug discovery.
- Effective contributing to collaborative projects involving cross-disciplinary and global teams.
- Awareness of graph modeling, machine learning, Bayesian analytics or other non-traditional approaches to model biological data.
- Expertise in genetic (DNA sequence, NGS) data interpretation.
- Python/Perl programming expertise.
- SQL/Database management expertise.
Next Steps – Apply today!
To be considered for this exciting opportunity, please complete the full application on our website at your earliest convenience – it is the only way that our Recruiter and Hiring Manager can know that you feel well qualified for this opportunity. If you know someone who would be a great fit, please share this posting with them.
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.