The Cortes-Ciriano group studies the mutational processes and mechanisms of genome instability underpinning tumourigenesis, immune escape, and drug response through the analysis of high-throughput sequencing data from clinical samples. The group is also leading the development of novel approaches for early cancer detection. More information about the group can be found here.
We invite applications for a Postdoctoral Fellow position in the fields of cancer genomics and long-read sequencing data analysis. We are looking for an intrinsically motivated, talented, and hypothesis-driven individual with experience in analysing high-throughput sequencing data sets. This position is an excellent opportunity for individuals looking to gain in-depth knowledge and expertise in genomic medicine and long-read sequencing data analysis. You will be expected to lead the development of scalable and creative computational solutions for sequencing data analysis. Specifically, your project will involve developing computational methods for analysing a unique collection of hundreds of long-read whole-genome sequencing data sets from human tumours spanning multiple cancer types, including adult and paediatric tumours. It is essential that you are dedicated to lead your own project while also being a team player and willing to engage with our national and international collaborators.
You will enjoy substantial freedom (if desired) to design novel algorithms and to explore your own hypotheses. Your project will benefit from close interactions with our clinical and wet-lab collaborators.
PhD degree in the life sciences (preferably computational biology, genomics, statistics, or a similar field)
Strong analytical and programming skills (preferably in python and R)
Significant experience in computational genomics (ideally in cancer genomics) as evidenced by publication record
Demonstrated ability to work both independently and collaboratively with other group members and external collaborators
Proficient communication skills in both written and spoken English
Experience in Unix-based environments, high-performance computing and the development of reproducible data analysis pipelines using version control software
Data science skills, such as visualisation of complex data sets
You might also have:
Background in cancer biology
Experience in long read sequencing data analysis is desired but not required
Benefits and Contract information:
Financial incentives: Monthly family and child allowances, stipends reviewed yearly, death benefit (optional), long-term care, accident-at-work and unemployment insurances
Flexible working arrangements
Private medical insurance for you and your immediate family (including all prescriptions and generous dental & optical cover)
Generous time off: 30 days annual leave per year, in addition to eight bank holidays
Campus life: Free shuttle bus to and from work, on-site library, subsidised on-site gym and cafeteria, casual dress code, extensive sports and social club activities (on campus and remotely)
Family benefits: On-site nursery, 10 days of child sick leave, generous parental leave, holiday clubs on campus and monthly family and child allowances
Benefits for non-UK residents: Visa exemption.
Contract duration: This position is a 2 year contract.
International applicants: We recruit internationally and successful candidates are offered visa exemptions. Read more on our page for international applicants.
Diversity and inclusion: At EMBL-EBI, we strongly believe that inclusive and diverse teams benefit from higher levels of innovation and creative thought. We encourage applications from women, LGBTQ+ and individuals from all nationalities.
DORA- EMBL is a signatory of DORA and is committed to hiring and training outstanding research, service, and administrative personnel.
This role is based in Hinxton, near Cambridge, UK. You will be required to relocate if you are based overseas and you will receive a relocation package to support you.
How to apply: To apply please submit a cover letter and a CV through our online system.