This is a full time, fixed term contract (4 years)
An exciting opportunity to be part of a pioneering biomedical research institute, dedicated to innovation and science, in the laboratory of Samra Turajlic (Cancer Dynamics, https://www.crick.ac.uk/research/labs/samra-turajlic). We are seeking a highly collaborative and self-motivated post-doctoral bioinformatician to work within our comprehensive tumour evolution programme, collaborating with a network of groups across The Francis Crick Institute, UCL Cancer Institute, the Institute of Cancer Research, as well as internationally, including NIH (US) and pharma. The position will involve analysis of data from large-scale tumour evolutionary trials such as the TRACERx and PEACE studies as well as interventional clinical trials, such as ADAPTeR and A-PREDICT and the 100KG Genomics England datasets. Our studies have underpinned a wide number of successful contributions to the field of tumour evolution and achieved an excellent track record of high impact output. This project sits at the interface of basic and translational research and will be utilising rich multi-omic datasets (bulk and single-cell) generated from large-scale trials run locally and internationally as well as pre-clinical models. Our focus is renal cell carcinoma and melanoma, however, some of the bioinformatics projects are also conducted in the pan-cancer setting, while others are focused on clinical adoption of biomarkers. The role is ideally suited for a creative individual with a strong interest in cancer genomics, cancer evolution, evolutionary biology, and bioinformatics in a leading academic setting.
The successful applicant will have a proven track record in cancer bioinformatics, with previous experience of NGS data analysis, and be fluent in at least one of the following programming languages: Python or R and is expected to have strong skills in genomics and in cancer biology and/or evolution. Prior experience with data analysis based on integrating large datasets is particularly desired. The position will be based within a multi-disciplinary team of cancer evolutionary biologists, wet-lab scientists and translational research clinicians concerned with both basic evolutionary principles and application of evolutionary rules in the clinic. We collaborate closely with colleagues specialising in machine learning and mathematical modelling. Further, the lab also has a strong focus on understanding anti-tumour immune response and tackling this through both wet lab and dry lab work. The applicant will have the opportunity to develop collaborations nationally and internationally, and there will be an opportunity to engage with our industry and academic partners. The candidate will work closely with other computational scientists at Francis Crick Institute and have ample opportunities to develop their skills. A comprehensive computational infrastructure is available, with access to multiple HPC clusters.
The proposed project leverages four programmes: TRACERx Renal (http://tracerx.co.uk/studies/renal/), NIH (https://grantome.com/grant/NIH/U01-CA247439-01) HOLST-F (https://www.annalsofoncology.org/article/S0923-7534(19)60107-9/fulltext), and PEACE (https://clinicaltrials.gov/ct2/show/NCT03004755, renal cancer and melanoma). The research is conducted in close collaboration with the Royal Marsden, Guy's and St Thomas' and Royal Free NHS Foundation Trusts and several international collaborators, including at the National Institute of Health, US. The candidate will focus on deciphering cancer evolution on the background of inherited VHL mutations- a rare opportunity to test the principles of evolutionary contingency in vivo; as well as in the context of sporadic kidney cancer, as a follow up to our interim report on the TRACERx Renal study (Turajlic et al. Cell 2018a&b). The analyses will involve normal and cancer tissues profiled at single cell and bulk level, both DNA &RNA; there will be further scope for in tissue transcriptomics approaches to be developed.
Dr Samra Turajlic is a Clinician Scientist with clinical practice in renal cell cancer and melanoma and the programme reflects emerging clinical questions tackled through a combination of cutting-edge methods. The overall aim of the lab is to yield fundamental biological insights, decipher the impact of selection and influence of the tumour microenvironment, immune system and cancer therapy on clonal evolution; and to apply this knowledge to improve patient outcomes. The successful applicant will be employed by the Francis Crick Institute and based within Dr Turajlic’s group, funded by Cancer Research UK, NIH, Melanoma Research Alliance, the Rosetrees Trust, and the NIHR Biomedical Research Centre, amongst others. The Francis Crick Institute offers an impressive computational infrastructure and additional resources are available through the CRUK City of London Centre and eMedLab, and there are ample opportunities for personal development.
Information about the work of the laboratory can be found through the links below:
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The primary duty of the post-holder will be to conduct bioinformatics discovery analysis, into the evolutionary drivers of metastasis and tumour progression, immune-escape and treatment resistance. The project will make use of what is thought to be one of the world’s largest datasets of genomic/transcriptomic data from several cancer evolution trials. Sequencing data is complimented by a wealth of supporting data-types, including histological, imaging data, clinical and radiomics data.
- To work within the bioinformatics team of the Turajlic lab, and collaborating groups at Francis Crick Institute and beyond, including academic and industry partners.
- To conduct analyses of genomic and transcriptomic data, using established pipelines.
- To analyse multi-region sequencing data, identifying somatic mutations, copy number aberrations and reconstructing phylogenetic trees.
- To employ novel informatics methods to apply to cell-free and single cell data including in-situ transcriptomics.
- To liaise and coordinate between the project collaborators which include clinicians, cancer biologists, machine learning experts and mathematical modellers.
- To document all analyses in an accurate, timely and clearly presented manner, and use this to prepare data summaries and reports as and when required.
- To understand tumour evolution and the relevant literature (cancer biology, cancer genomics) sufficiently to propose novel ideas.
- To drive the project forward through making biological insights, integrating them with pre-clinical models and clinical studies and generating new hypotheses
- To attend, and report research results at regular group meetings.
- To contribute to the dissemination of scientific results by means of writing papers for publication and presenting orally and in poster form at national and international meetings.
- To contribute to the broader research programme of Turajlic lab intellectually and practically
- To support junior colleagues as necessary
- Any other duties appropriate to the scope and grade of the post. The job description may be subject to review and amendment in consultation with the post holder as job duties change/develop
Key Experience and Competencies
- PhD in bioinformatics or a relevant discipline
- Prior experience in cancer genomics would be preferred
- Fluent in shell scripting and at least one of the following programming languages: R or Python
- Excellent general computational skills
- Understanding of mathematics and statistics
- Evidence of independent and original contribution to research
- Ability to manage projects setting timelines, analysing, presenting and writing up the conclusions
- Excellent presentation skills- including at international conferences
- Ability to represent the PI at meetings and conferences
- Excellent inter-personal skills and commitment to teamwork
- Ability to work with minimal supervision using own initiative to organise and prioritise own work
- Ability to define and solve research questions
- Pro-active in innovation and problem solving
- Experience in the field of evolutionary biology/cancer evolution is desirable
- Experience with single-cell sequencing and imaging analyses is desirable
- Experience with Nextflow or similar pipeline management frameworks is desirable
- Experience with machine learning is desirable
- Previous experience of multidisciplinary working is desirable