Principal Bioinformatician I – Cancer Dynamics Laboratory
Reports to: Samra Turajlic, Group Leader
This is a full-time, fixed term (2 years) position on Crick terms and conditions of employment.
We are seeking a collaborative and self-motivated bioinformatician to spearhead cancer evolutionary genomics analysis and the design and operation of the bioinformatics next generation sequence pipeline for the TRACERx Renal cancer and associated programmes at the Francis Crick Institute, in the Cancer Dynamics Laboratory. The role is ideally suited for a creative individual with a strong interest in cancer genomics, cancer evolution, software development and testing, database analysis, and automation within a high throughput academic setting interested in working at the Francis Crick Institute. We seek a candidate with strong software engineering and programming skills who is keen to apply these skills to the field of cancer genomics and cancer evolutionary biology. The successful applicant will have previous experience with NGS data analysis, be fluent in at least one of the following programming languages: Python or R, and is expected to have strong skills in the field of genomics and desirably one or more of the following: cancer biology, evolutionary biology, statistics, mathematics or machine learning. Prior experience with data analysis based on integrating large datasets is particularly desired.
Dr Samra Turajlic is the Chief Investigator of the TRACERx Renal initiative (http://tracerx.co.uk/studies/renal/), a largescale longitudinal genomics study in renal cancer utilizing deep multi-region tumour sequencing. Additional translational studies are HOLST-F (NCT03832062) and PEACE (NCT03004755, renal cancer and melanoma), both providing unique windows into cancer progression. The focus of the overall lab programme is the investigation of cancer evolution and the development of high throughput bioinformatics techniques to decipher cancer mutational processes, tumour microenvironmental signals and tumour evolutionary trajectories through the disease course. The candidate will be expected to work within the existing Turajlic lab informatics team and collaborating informaticians at the Crick, and utilise evolutionary, mathematical and statistical methods to deconvolute cancer evolution based in particular but not exclusively upon next generation sequencing data. In addition, the candidate will be expected to have multidisciplinary skills working with clinical and scientific staff and support them in their learning and development.
The successful applicant will be based in a multi-disciplinary team of cancer evolutionary biologists and translational research clinicians concerned with both basic evolutionary principles and application of evolutionary rules in the clinic. In addition, our group have multiple collaborations nationally and internationally, and there will be an opportunity to engage with our industry and academic partners. The candidate will collaborate with other computational scientists at the Francis Crick Institute and have ample opportunities to develop their skills. The Francis Crick Institute offers an impressive computational infrastructure and additional computational resources are available through the CRUK City of London Centre and the MRC eMedlab.
These include but are not limited to:
Lead on the running and development of the NGS analysis pipelines.
- Evaluate and provide software, databases, protocols and methods to aid in the analysis of genomic and genetics experiments from academic and commercial sources.
- Develop methodologies and techniques to address analysis issues and implement software and data resources in relation to these technologies.
- Lead the bioinformatics analysis of projects with a view to high impact publications investigating cancer evolution and the interface with the immune microenvironment and novel profiling methods.
- Provide consultation and communication in data analysis, statistics, genomics and other areas of bioinformatics, to other members of the team.
- Produce thorough but concise written documentation of algorithms, validations, SOPs, and other processes and procedures as required.
- To liaise and coordinate between various working groups involved in the sequencing of clinical samples to ensure the delivery of high-quality sequence data in a time efficient manner.
- To record all experiments in an accurate, timely and clearly presented manner, and use this to prepare data summaries and reports as and when required.
- To attend, and report research results at regular group and (inter)national meetings.
Key experience and competencies
The post holder should embody and demonstrate our core Crick values: bold, imaginative, open, dynamic and collegial, in addition to the following:
Qualifications, experience and competencies:
- Higher degree in a relevant subject with an extensive analytical component e.g. bioinformatics, statistics, molecular biology
- Fluent in at least one of the following programming languages: Python or R
- Familiarity with the application of statistical techniques to biological data
- Considerable experience of using bioinformatics in a biological field, ideally translational research projects
- Demonstrable experience of NGS analysis methodologies and protocols
- Experience of interaction with investigators on scientific projects and working in a collaborative environment
- Experience of managing a large analysis project over a number of years is desirable.
- Works with minimal supervision, organising and prioritising own workload
- Excellent communication skills within a research environment, building highly effective working relationships with team and customers.
- Excellent scientific analysis skills
- Evidence of independent and original contribution to research
- Ability to manage projects to timelines, analyse, present and write up data in a timely manner
- Good presentation skills
- Excellent inter-personal skills and commitment to team-work
- Experience in the field of evolutionary biology/cancer evolution is desired
- Experience with machine learning is desirable
Qualifications, experience and competencies:
- An understanding of programming, particularly with regard to big data, data visualisation and data-mining techniques within a genomic or genetical environment
- Knowledge of genetics, model organisms, cancer biology
- A broad comprehension of high throughput genomic technologies
- Experience of having managed a large bioinformatics project
- Experience of supervising or mentoring other members of the team
- Experience of monitoring and allocating resources within a project