BACKGROUND

RESPONSIBILITIES

• Lead development of innovative approaches to genome sequence analysis to provide a bespoke bioinformatics pipeline for alignment, calling, annotation and interpretation of single nucleotide, copy number, non-coding and structural variants from human genome sequence data.
• Conduct analysis of genome sequencing data from rare disease and cancer patients incorporating other `omics data sets (eg transcriptomics, metabolomics) as required, to support a comprehensive assessment of variants.
• Explore opportunities to develop and apply machine learning approaches to explore complex patterns in the genome sequencing datasets available to the group.
• Conduct independent research projects in development of novel bioinformatics tools and algorithms and/or contribute to disease specific research projects within the group, identifying emerging areas of research.
• Play a leading role in the contribution to the UK's national Genomics England (GEL) 100,000 Genomes programme, through analysis and interpretation of GEL data. Collaborate with GEL bioinformaticians and Oxford PIs and provide bioinformatics expertise on Genomics England Clinical Interpretation Partnerships (GeCIPs)
• Supervise a growing team of bioinformaticians and research scientists undertaking WGS data analysis. Co-ordinate activities and meet with members on a regular basis to ensure familiarity and consistency of methods and utilisation of pipelines. Provide motivation and supportive leadership in a team working environment.
• Take responsibility for maintaining the bioinformatics pipeline and ensuring standards of quality and version control are attained.
• Write up research results for publication in high quality journals and present these at national/international meetings. Lead applications for grant funding in own research area.
• Identify and evaluate methodology developments relevant to the field, including evaluation of commercial or other software packages for analysis, annotation and interpretation of sequencing data, and integrate with existing data analysis pipelines.
• As appropriate for the projects, lead the translation of bioinformatics pipelines into clinical use, liaising with clinical teams to achieve this.
• Communicate frequently and effectively with project teams, including laboratory scientists, clinicians and PIs, to discuss the bioinformatics requirements of projects, report data, review results and ensure that the tasks are completed satisfactorily.
• Participate in lab group meetings and contribute to discussions at these.

REQUIREMENTS

• A PhD in Bioinformatics or Statistical Genetics
• Strong postdoctoral experience in analysis, annotation and interpretation of genome sequencing data to include single nucleotide and structural variants, copy number abnormalities as well as assessment of variants in regulatory or non-coding regions. Experience of a wide range of publicly accessible resources and databases to support this
• Excellent programming skills in languages such as Perl, Python, Java, C/C++, R or similar
• Experience of supervising bioinformaticians and/or lab scientists and clear evidence of developing and managing collaborative teams
• Proven ability to develop novel bioinformatics tools and algorithms for analysis of genetic data
• Experience of implementing, improving and maintaining bioinformatics pipelines and troubleshooting problems. Demonstrating experience of developing quality and version control standards and secure data management
• Familiarity with protein informatics to inform assessment of impact of variants on proteins' secondary and tertiary structures, protein-protein interactions and protein expression
• Track record of independent research with proven ability to write up scientific findings in peer-reviewed journals and in contributing to grant applications
• Demonstrable experience of assessing new developments in the field, including commercial software packages and applying them efficiently
• Willingness to provide bioinformatics leadership for the Theme's contributions to national collaborative programmes including Genomics England and DDD and analyse data within the environments and according to the regulations of these programmes
• Excellent communication skills (both written and oral) with the ability to communicate effectively at all levels (of technical knowledge)
• A high degree of self-motivation and initiative and ability to both work independently and as a team member to meet project deadlines
• Familiarity with expression and pathway analyses
• Experience with analysis and integration of multi-omics datasets including RNASeq and metabolomics
• Success in being awarded grant applications to support research projects

HOW TO APPLY