Postdoctoral Computational Biologist

King's College London - Comprehensive Cancer Centre

About us:

This Computational Biologist post forms part of the CRUK City of London Centre and is based within the School of Cancer & Pharmaceutical Sciences at King’s College London. The successful candidate will be embedded in Professor James Arnold’s Tumour Immunology Group, where they will contribute to and support the development of ongoing research projects across the School, in a collaborative academic environment.

About the role:

The post is offered as a full-time, fixed-term contract for an initial period of one year.

The successful candidate will develop and implement novel analytical pipelines for high-dimensional datasets, including spatial bulk and single-cell RNA sequencing, mass and flow cytometry, and imaging data derived from both patient samples and experimental models. The overarching aim of the role is to support efforts to deconstruct the tumour microenvironment and elucidate its role in cancer, generating new biological insights and identifying novel and unexpected therapeutic opportunities.

The post will be primarily based at Guy’s Campus. The successful candidate will work closely with Professor James Arnold to support and further develop ongoing research activities within the School in a highly collaborative academic environment. The role will also involve training and supervising PhD students and junior research associates in the application of bioinformatics tools. More broadly, the successful candidate will benefit from, and contribute to, the interdisciplinary research culture and extensive academic networks at King’s College London.

About you:

To be successful in this role, we are looking for candidates to have the following skills & experience:

Essential criteria

1. Candidate must have (or be studying for) a PhD in a relevant field of research; ideally in the computational and/or biology and/or cancer field.
2. Demonstrable knowledge and prior work with spatial and RNA-seq datasets in a biological context.
3. Strong software and data processing skills: experience of programming in one or more languages (e.g. R, C/C++, Python, Matlab).
4. Practical experience of algorithm development and implementation of machine learning approaches.
5. Experience in writing scientific manuscripts and peer reviewed publications.
6. Ability to work as part of a team, in a collaborative fashion between teams and willingness and ability to exchange information with team members and internal and external contacts

Full details of the role and the skills, knowledge and experience required can be found in the Job Description document.