Summary
The Surgical Research Laboratory is looking to appoint a highly skilled individual to play a key role in analysis of next generation sequencing data from the Cancer Research UK funded translational medicine programme, DETERMINE. The DETERMINE programme aims to understand the rationale behind response to targeted agents outside their licensed indication using long read Nanopore sequencing, as well as spatial transcriptomics, circulating tumour DNA assays and multiple immunohistochemistry.
The successful candidate will also support analysis of a wide range of data types analysed by the laboratory including long and short read WGS, targeted sequencing and RNAseq, single cell sequencing, optical genome mapping and CRISPR dependency screens. Ideally you will have previous experience as a cancer bioinformatician, however we are willing to support the right candidate with a computer science or bioinformatics background to gain these skills as part of the research group. The candidate will be exposed to a wide range of ‘omics data types and will gain experience in their analysis. This is a singular opportunity for a motivated candidate to gain experience in the analysis of long read sequencing in one of the highest volume laboratories for Nanopore sequencing in the world, across a wide range of datasets.
As such, we are looking for a highly motivated, self-sufficient and enthusiastic bioinformatician who enjoys working in a “team science” environment on a range of different projects. These attributes are most important to us, as post specific skills can be taught to the right individuals if we feel they are the best candidate. We are particularly looking for applications from women, and under-represented ethnic groups within science.
A practical test will be carried out as part of the interview on a test NGS dataset in a restricted compute environment to assess knowledge.
Main Duties
1. Create pipelines to process, analyse, and integrate multiple (epi)genomics/transcriptomics sequencing and other related experiments
2. Present results of cohort analyses in order to help derive insights into datasets.
3. Apply machine learning methods to integrate multi-omics data with real-world clinical outcomes data.
4. Provide assistance to the research group in dataset management, upload to public repositories and general data management duties
5. Liaise with collaborators of the research group on all bioinformatics related matters
6. Contribute to Centre/Institute research-related activities and research-related administration
7. Contribute to enterprise, business development and/or public engagement activities of manifest benefit to the College and the University, often under supervision of a project leader
8. Collect research data; this may be through a variety of research methods, such as scientific experimentation, literature reviews, and research interviews
9. Present research outputs, including drafting academic publications or parts thereof, for example at seminars and as posters
10. Provide guidance, as required, to support staff and any students who may be assisting with the research
11. Deal with problems that may affect the achievement of research objectives and deadlines
12. Carry out administrative tasks related directly to the delivery of the research
13. Promotes equality and values diversity acting as a role model and fostering an inclusive working culture
Person Specification
14. Degree in bioinformatics, computer science, physics or mathematics, and preferably, a higher degree relevant to research area or equivalent experience.
15. High degree of computer literacy
16. Comprehensive experience in Linux / HPC computing environments, including Slurm job scheduling systems and Nextflow, Cloud environments (ideally AWS including deployment) and be proficient in understanding the practicalities of TCP networking and data transfer frameworks
17. Understanding of next generation sequencing datasets, including their structure and theoretical basis.
18. Practical, demonstrable experience in: R, Bioconductor, Python, Java, DNA/RNA alignment software (. BWA, Minimap), variant calling methodologies (. GATK Toolkit, hmftools, long read tools) and cohort analysis.
19. Experience of development of machine learning models using either Python/R within appropriate frameworks would be desirable but is not essential.
20. Ability to proficiently code in C/C++ would be an advantage but is not essential.
21. Ability to communicate complex information clearly and the ability to communicate with non-experts in bioinformatics to reach project goals.
22. Ability to access and organise resources successfully
23. Experience of managing scientific projects.
24. Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day to day activity in own area that those with protected characteristics are treated equally and fairly