MRC Postdoctoral Research Scientist in Computational Genomics/Bioinformatician LMS 2551

MRC Laboratory of Medical Sciences

The LMS is a world-class research laboratory where scientists and clinicians collaborate to advance the understanding of biology and its application to medicine. Funded by the MRC as part of UK Research and Innovation, the LMS has a collaborative working culture and new state-of-the-art building based in the heart of West London in the Hammersmith Hospital Campus (W12).

The LMS aims to deliver transdisciplinary team science, in synergistic interaction with Imperial College and the wider national research environment. Part of achieving this, is to recruit new talent and support postdoctoral scientists to become world leaders in their area of science.

MRC – 4

London

£41,344 plus London allowances (£5,385) per annum

Additional allowances comprise a £1,000 lump sum Settlement Allowance plus a yearly Training Allowance of £850 in the first year, paid in monthly instalments. The Training Allowance increases to £1,300 in year two, and £1,800 in the third year.

Fixed Term

Science

Full Time

3 years

Overall purpose:

The Genomic Variation and Disease Group works at the intersection of medical genetics, cancer genetics, bioinformatics, and molecular biology to identify potential SV-derived therapeutic targets in cancer. The group uses genomics, RNA-sequencing, and proteomics, with the MRC LMS cutting-edge core facilities, in combination with computational approaches to characterize SV-derived neo-peptides with immunogenic potential, opening up potential immunotherapies in cancer.

We are looking for a talented postdoctoral scientist with a background in computational biology (bioinformatician) to join our team. As a key member, you will be part of our collaborative effort to identify potential SV-derived therapeutic targets in cancer. Your work will involve analyzing genomics (whole genome sequencing (WGS) and 3D chromatin interactions), transcriptomics (single-cell and bulk RNA-sequencing), and proteomics data to identify potential SV-derived neo-peptides with immunogenic potential.

At our newly established lab, we are committed to creating a welcoming and supportive environment where people of all backgrounds can thrive. We value diversity and collaboration and focus on conducting cutting-edge basic and translational science. At the LMS, we also offer excellent mentoring and support to help you reach your career goals. As a post holder, you will have the opportunity to work with an extensive network of collaborators, attend scientific conferences, and publish the results of your work in refereed journals. To provide the adequate scientific environment for your career progression, you will be embedded within the Computational Regulatory Genomics research group headed by Professor Boris Lenhard (https://lms.mrc.ac.uk/research/computational-regulatory-genomics/). You will also work closely with the Systems Immunology research group headed by Professor Petter Brodin (https://lms.mrc.ac.uk/research/systems-immunology/).

Key skills:

• Background in computational biology
• Background in cancer genetics an advantage
• Experience of handling large sequencing datasets
• Experience of analyzing whole genome sequencing and bulk RNA-sequencing datasets
• Experience of analyzing 3D chromatin interaction, single-cell RNA/DNA-sequencing, and proteomic datasets an advantage
• Excellent programming skills in R and Python
• Knowledge of HPC environments an advantage
• A record of accomplishments indicating the ability to analyse, visualise and disseminate data produced by high-throughput sequencing, as well as in-depth knowledge of molecular biology

Main Responsibilities:

• To lead analyses to identify potential SV-derived therapeutic targets in cancer
• To manage large datasets
• To collaborate closely with other members of the team on various projects
• To prepare work for publication and grant submissions
• To present at seminars and conferences as necessary
• To co-supervise MSc and PhD students
• To contribute to the smooth running of the Group’s/Unit’s laboratories and facilities with other scientists, clinicians, technicians and students within the laboratories
• To comply with the Institute, College, Division, and Unit safety practices and to attend courses on safety when appropriate

Any other duties as may be deemed reasonable by Head of group as well as Head of Division

Education / Qualifications / Training required (will be assessed from application form):

Essential:

• PhD (or equivalent) in computational biology/bioinformatics or a closely related discipline

Knowledge and experience (will be assessed from application form and at interview):

Essential:

• Experience in computational biology/bioinformatics
• Experience planning and completing research projects demonstrated through relevant publications and presentations
• Expertise in genomics and/or experience in analysis of next generation sequencing data (whole genome sequencing and RNA sequencing)
• Excellent written communication skills in English and the ability to write clearly for publication

Desirable:

• Experience in cancer biology
• Knowledge of databases and resources for structural variant annotation
• Experience of analyzing 3D chromatin interaction, single-cell RNA/DNA-sequencing, and/or proteomic datasets

Personal Skills / Behaviours / Qualities (will be assessed at the interview):

Essential:

• Ability to conduct reproducible research
• Ability to conduct a detailed review of recent literature
• Ability to develop and apply new concepts
• Creative approach to problem-solving
• A keen interest in learning new skills
• Excellent verbal communication skills in English and the ability to deal with a wide range of people
• Ability to motivate others to produce a high standard of work
• Ability to organise own work with minimal supervision
• Ability to prioritise own work in response to deadlines
• Advanced computer skills, including word-processing, spreadsheets and the internet
• Willingness to work as part of a team and to be open-minded and cooperative
• Flexible attitude towards work
• Discipline and regard for confidentiality and security at all times
• Willingness to undertake any necessary training for the role

Applicants should submit a CV, names and contacts of two scientific references along with a cover letter stating why you are applying for this role (providing evidence against the requirements of the job as per the job description and person specification). Applications without a cover letter will not be accepted. Please quote reference number LMS 2551.

This role qualifies for endorsement by UKRI for a UK Global Talent Visa, for which the successful applicant is likely to be eligible to apply. We will also reimburse the cost of visa application (terms and conditions apply).

Please note that applications may be reviewed by both LMS and Imperial staff