Research Fellow (Single Cell Computational Biology)

Job Purpose

The post holder will develop and establish a research programme in single cell computational biology with a particular focus on cancer, and the utility of state-of-the-art statistical machine learning techniques.

The post holder will work with selected collaborators, drawn from the large base of internationally recognised biomedical research expertise from across the portfolio of the University of Birmingham and associated Hospital Trusts, to design and implement computational statistical methodologies; advancing our understanding of human disease and fundamental biology. With a particular focus on single cell perturbation biology using CRISPR genome editing techniques, the role will require the application of statistical and computational modelling skills to translate complex biological problems into a quantitative form. The post holder will use computational skills to implement statistical algorithms using modern computer programming languages and to use these to analyse data sets and interpret the results. Strong presentation and communication skills are required to convey complex information to both technical and non-technical experts.

The post holder will be embedded within the new Statistical Machine Learning in BioHealth group, led by Dr Christopher Yau at the Centre for Computational Biology. The post holder will also work in collaboration with clinician scientist Dr Andrew Beggs who has established an experimental programme in Single Cell Genomics. The Genomics Facility at the University of Birmingham has access to state-of-the-art sequencing and single cell platforms from Fluidigm and 10X Genomics. The Genomics Facility will play a leading role in the continued single cell computational biology work of the Statistical Machine Learning in BioHealth group.

Person Specification

• A first degree and PhD in a substantially quantitative subject including Mathematics, Statistics, Physics, Engineering or Computer Science.

Ability to:
• To demonstrate an understanding of both science and informatics in a biomedical and clinical setting.
• Innovate and develop ideas into grant proposals
• To learn and keep abreast of latest technological, methodological and software developments.
• Ability to write concise and timely scientific papers and reports Must be able to plan and prioritise work effectively to meet deadlines
• Substantial experience of statistical modelling gained within a research setting
• Experience of algorithmic development for statistical computing
• Expert proficiency in modern low-level and high-level programming languages
• Experience with the analysis of biomedical data (e.g. electronic health records, genomic data) would be advantageous.