In collaboration with a major pharmaceutical partner, King's College London is launching a substantial programme of basic and translational research into understanding the early molecular and immunological events that lead to the establishment Clonal Haemopoiesis and early stages of Myelodysplastic Syndrome (MDS). Comparison of these early events with subsequent molecular phenotypes of MDS and Acute Myeloid Leukaemia (AML) should help to identify targets for therapeutic intervention.
It is anticipated we will recruit over 6,000 patients undergoing hip replacements as a healthy ageing cohort for the study to follow for at least 5 years; continuing to observe changes to health and haematology profiles. The programme aims to build one of the largest Biobanks to interrogate associations between immune and genetic changes in the blood and diseases that increase in prevalence with age and to enable future translational research endeavours. There is therefore an urgent need to develop reliable tools for patient stratification in order to ensure that only those likely to benefit are given a specific treatment.
The post holder will contribute expertise in applying technologies of all types associated with the stratification of patients for immune-oncology treatments. As part of this job, the post holder will contribute in designing a major database, developing pipelines to analyse and integrate multiple biological research and clinical data streams, and generating insights that drive the elucidation of key disease mechanisms. The project involves (and not limited to) multi-omic (Genomics, single-cell RNAseq, ChIP-seq, Methyl-seq, metabolomics, and microbiomics) and mass-cytometry (CyTOF) data analysis of blood samples.
Specific Research Responsibilities:
- To process, organize, interpret, and disseminate genomics and immunological data coming from KCL/Celgene research project
- To perform omics analysis that drives better understanding of disease etiology and biomarker discovery and treatment response
- To create, implement and use analytical and bioinformatics pipelines to analyse and interpret multidimensional data.
- To work on agreed aspects of specialized bioinformatic analyses in accordance with project workstream requirements and deliverables.
- To work on data flow, storage, dissemination, including cloud datahub development.
- To develop advanced data manipulation and analysis capabilities using R/Bioconductor, Matlab, Python, and open-source bioinformatic tools and database structures to analyse complex data from EHRs, omics, and functional measures.
- To support grant writing, for maintaining the continual research in this domain.
General Research Responsibilities:
- To communicate bioinformatics analysis to postgraduates, research scientists and principal investigators.
- To ensure the validity and reliability of data and methods at all times.
- To maintain accurate and complete records of analysis projects.
- To identify and develop suitable techniques for the analysis and visualisation of data, and to build and maintain the associated computational resources (software packages, databases, or web-based analysis and visualisation tools).
- To maintain all code and programs used for analysis and tool development with suitable source control.
- To identify and implement present and upcoming infrastructure requirements for the Bioinformatics team.
- To assist in and develop bioinformatics training for postgraduate research students and research assistants.
- To comply with the College, Division, and Unit safety practices and to attend courses on safety when appropriate.
Skills, knowledge and experience
- MSc or PhD awarded in Bioinformatics, Biostatistics, Computer Science, Biotechnology or relevant discipline
- Knowledge of relevant platforms and techniques
- Knowledge of computational biology
- Advanced skills in the analysis of Genomics data (like whole-exome and targeted-exome sequencing data) involving (but not limited to) variant calling, annotation, functional characterization and assessment of association with disease
- Past peer-reviewed publication(s) that involves the analysis of genomics NGS data, bulk/single-cell transcriptomics data, CyTOF data, and/or web programming and database development.
- Proficiency in at least one general programming language (R, Python, Java or C++ are preferred)
- Skills in statistical analysis of data/modelling in R or similar
- Skills to develop novel tools using statistics, mathematics and/or machine learning approaches for the analysis of high dimensional data
- Interest in the field of translational cancer research
- Experience in bioinformatics techniques and tools in the analysis of high dimensional biological data
- Experience in pipeline scripting, automation and management in HPC clusters
- Advanced skills in processing bulk and single-cell transcriptomics data
- Ability to analyse CyTOF data with existing publicly available and commercial software solutions (e.g. R/Bioconductor, UMAP, viSNE, SPADE, FlowJo, CytoBank suite)
- Knowledge of immunology, any previous lab experience is advantageous
- Experience in web programming
This advertisement does meet the requirements for a Certificate of Sponsorship under Home Office regulations and therefore the university will be able to offer sponsorship for this role.