Featured RNA-Seq Job – Senior/research scientist, single cell RNA-sequencing data analysis

Would you like to apply your expertise interrogating single-cell and/or single-nuclei transcriptomics data to identify new drug targets for cardiometabolic disease?  Are you motivated by being part of a multi-disciplinary team committed to having fun while working with cutting-edge data to address hard problems?  Then you may be the new colleague we are looking for to join our early-stage drug target discovery efforts in the Novo Nordisk Research Centre, Oxford (NNRCO).

About the department

You will join the Computational Biology team at NNRCO, located at Oxford University’s Old Road Campus. The group boasts significant expertise across a diverse set of disciplines in computational biology, bioinformatics, and machine learning; not least multi-omic data integration, systems biology, and knowledge-graphs.

In addition to staff scientists, our group hosts and collaborates with researchers from Oxford University and we undertake several ambitious academic and in-house projects.  Our focus is drug-target identification and providing insights from heterogenous data sources.

The Department is anchored in the newly established Digital Science & Innovation organisation within Research & Early Development at Novo Nordisk, and benefits from integrated collaborations across the company as well as with strategic external academic and industrial partners.
The Role

You will perform cutting edge analyses of high-throughput single-cell functional genomics data to identify new drug targets for cardiometabolic disease. This includes a range of in-house projects and academic collaborations with Oxford University researchers. To get us there, you will leverage your expertise in single-cell and single-nuclei RNA-seq and multi-omics data analysis to discover novel biology and progress exciting new drug targets through the company’s extensive pipeline.

To do this we expect you to have:
•    substantial experience analysing single-cell/-nuclei RNA-seq data and integrating with other omics
•    independently driven analysis projects and contributed biological insights gleaned from these analyses to peer-reviewed publications
•    the insight and drive to put these findings in context of genetics, pathways, and protein-protein interactions.

Under the guidance of senior research staff across NNRCO you will:
•    have the freedom to identify and champion novel drug targets and engage with in-vitro scientists to validate your findings
•    assist the in-vitro teams with their development of novel assays where you will help design and develop data processing pipelines
•    advise on experimental design
•    partner with our high-throughput phenotypic assay teams for appropriate data analyses

We are looking for someone who thinks the above sounds exciting and is motivated by keeping pace with developments in computational, molecular, and cellular biology.
Success is demonstrated on several levels including contributing to projects and analyses undertaken by the group, mentoring junior scientists, proposing, and presenting new target candidates, and liaising with academic collaborators.

Your Qualifications

You will have a PhD and postdoctoral experience in computational biology or similar discipline.
•    You will have strong programming skills in Python/R/Julia, substantial high-throughput computing experience, and be comfortable working in a Unix environment
•    You thrive working in tight multi-disciplinary teams to extract actionable insights from single-cell and/or single-nuclei experiments.
•    You have independently driven projects, preferably in collaborative settings, leading to publication and/or presentation in international-level journals or conferences.
•    You are conscientious and able to contribute to a positive working environment on site.

Additionally, strong candidates will have experience with statistics and machine-learning, including familiarity with high-performance computing (optionally including cloud computing).  Prior experience working in industry or clinical contexts is also valuable.


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