Principal Research Scientist, Computational Genomics Lead for Oxford Research Site

Vertex
Oxford
8 months ago
Applications closed

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Job Description

To advance the development oftransformativetherapies for people with serious and life-threatening diseases,we are seeking a computational biology leaderwithexpertisein making biological discoveries byleveraginglarge-scale genomicand geneticdataThis position is part of a global Computational Genomics team that designs and analyzes genomic studiesto advanceVertex’sdrug discoveryprograms. As the Computational Genomics lead(individual contributor)at Vertex’s Oxford UK Research site, you will collaborate closely withthe Oxford Research groupindesigningandexecutinggenomic studies,toimpactmultiple diseaseprojectsacross the drug discovery pipelineusing genomics. Example areas of impactincludetargetvalidation,pre-clinicalmodelcharacterization,andunderstanding mechanisms of actions of novel therapeuticsYour keyrolewill be tointerfacewith leadership and diseaseprojectteamstoalign on the priority and design of genomic studies, with the aim ofadvancingthe diseaseresearchprogramsat the OxfordResearchsite. You will also collaborate closely with thebroaderComputationalGenomics teamacross Global Researchtodrive the execution of genomic studies through best-practice computational analyses. This is an on-site or hybrid eligible position based out of our site in Oxford, UK, requiring at least 3 days/week onsite. 

 

Key responsibilities: 

  • As the Computational Genomics leadfor theOxfordresearchsite,proactivelycollaboratewithOxforddiseaseproject teamstoidentifykey projectquestions or challengesthat can be answeredusing genomics, sequencing, or bioinformatics contributions. This is an individual contributor role with no direct reportsat this time.   

  • Partner withComputational Genomics leadsat ourBoston and San Diegotoprioritizeglobal computational genomic needs to maximize impactacrossthe global research portfolio. 

  • Serve as the accountableleadforthe execution of prioritized computational genomic activities in the Oxford UK research siteInterface with Oxfordleadershipto provide regular progress updates. 

  • Perform advanced computational analyses oflarge-scalesequencing data and other biological data, through deep critical thinking, published findings and best practices from the field, strong statistics, and data science visualizations.  

  • Distil complex analyses and scientific results into key take-home messages and recommendations for next steps to a broad audience. 

  • Partner across global computational genomics team to develop guidelines for best practices for key genomic analyses. 

  • Partner withgenomics method development team and global computational genomics leadership to prioritize, develop, and evolve computational methods. 

 

Minimum Qualifications: 

  • Relevant education in computational biology, bioinformatics, human genetics, genomics, systems biology, bioengineering, or a related field, and relevant industry or post-doctoral experience.   

  • A proventrack recordin the analysis, visualization, and interpretation of large-scale human genetic data in a drug development context. 

  • Demonstrated ability to work across cross-functional teamsto designand implementexperiments, andexecutecomputational analysis. 

  • Expertisein applying computational methods and bioinformatics tools to large-scale data;proficiencywith R or Python, Linux/Unix systems, and high-performance computing systemsExperience with workflow language and cloud computing is a plus.

  • Solid understanding of statistics and genetics, including the role of geneticvariationin human disease.

  • Demonstrated ability to work across cross-functional teams, ensuringtimelyprogress.

  • Excellent presentation and communication skills, including the ability to tailor scientific content to audiences withdifferent backgrounds.

  • A team-oriented growth mindset that welcomes feedback from others and supports other team members; a positive attitude that enthusiastically tackles and overcomes challenges. 

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