Postdoctoral Genomics Data Lead in Cancer Evolution

THE INSTITUTE OF CANCER RESEARCH; England; On-site; GBP 35,000 - 55,000; Full time

Benefits offered by this job

Dynamic research environment

State-of-the-art facilities

Collaboration with leading researchers

Competitive salary and pension

Job summary

The Institute of Cancer Research seeks a Postdoctoral Training Fellow to contribute to the Boomers project, leading data generation and performing molecular genomic analyses on archival tumours from the 1950s to today.

The successful candidate will work in a highly interdisciplinary team, applying computational tools to infer tumour age and growth rate, and explore how mutational landscapes and microbiomes have evolved through the decades in order to inform prevention and treatment strategies.

Qualifications

• PhD in molecular biology or bioinformatics or other relevant area.
• Hands-on expertise in generating next-generation sequencing data.
• Appropriate publication record for level of experience.
• Good communication, observation and time-management skills, and ability to interact effectively with other team members in a highly interdisciplinary team.

Responsibilities

• Lead data generation for the Boomers project and perform molecular genomic analyses on archival tumours.
• Apply novel computational tools to infer tumour age and growth rate.
• Collaborate with dry-lab colleagues to explore mutational landscape and microbiome changes across decades.

Skills

PhD in molecular biology

Sequencing data generation

Publication track record

Interdisciplinary communication

Education

PhD in molecular biology or bioinformatics

Job description

The Institute of Cancer Research seeks a Postdoctoral Training Fellow to contribute to the Boomers project, leading data generation and performing molecular genomic analyses on archival tumours from the 1950s to today.

The successful candidate will work in a highly interdisciplinary team, applying computational tools to infer tumour age and growth rate, and explore how mutational landscapes and microbiomes have evolved through the decades in order to inform prevention and treatment strategies.