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Position: Genomics Statistician/Analyst
Institution: Institute of Cancer Research
Department: Clinical Studies
Location: London, United Kingdom
Duties: Your work will focus on the development and validation of hypotheses and the generation of molecular markers of breast cancer. An important component of the role will be using tools and software packages that enable reproducible research and develop statistical methods for efficient data analysis. You will assume a key position performing statistical modelling/analysis of in-house (as well as publicly available) next generation sequencing datasets such as Exome, Targeted and Whole genome sequencing, and RNA sequencing datasets, and correlating the results to patient outcome
Requirements: In addition to a first degree in a subject with strong statistical/mathematical components, the successful applicant will hold a post-graduate qualification in bioinformatics, statistics, computer science, engineering or mathematics. Your analytical experience will enable you to perform integrated analysis. You will also have gained significant experience in bioinformatics role/s, data analysis and related statistical methodologies, have undertaken training and have an interest in clinical trials, genomics or related fields
   
Text: Genomics Statistician/ Analyst Closing Date 21/10/2018, 23:55 Location Sutton Division Clinical Studies Team Genomic Analysis - Clinical Trials Vacancy Type Full time Type of Contract Fixed Term Length of Contract 3 years Hours per Week 35 Salary Range £35,109- £42,634 The Institute of Cancer Research, London, is one of the world’s most influential cancer research institutes, with an outstanding record of achievement dating back more than 100 years. We provided the first convincing evidence that DNA damage is the basic cause of cancer, laying the foundation for the now universally accepted idea that cancer is a genetic disease. Today, The Institute of Cancer Research (ICR) leads the world at isolating cancer-related genes and discovering new targeted drugs for personalised cancer treatment. Under the leadership of our Chief Executive, Professor Paul Workman FRS, the ICR is ranked as the UK’s leading academic research centre. Together with our partner The Royal Marsden, we are rated in the top four cancer centres globally. The ICR is committed to attracting, developing and retaining the best minds in the world to join us in our mission - to make the discoveries that defeat cancer. Vacancy Description Do you have a desire to develop novel statistical methods to molecular data for clinical development? Are you interested to apply new machine learning and computational methods to integrate genomics data with clinical data? Do you want to work in a multidisciplinary setting in an established clinical trials unit? Do you want to develop a career in biostatistical research, specialised in genomics data? We are seeking a talented, highly motivated individual with a background in Computational Genomics/Statistics to join the newly-formed Genomic Analysis - Clinical Trial group headed by Dr Cheang, co-inventor of PAM50 classifier for breast cancer intrinsic subtypes, based at the ICR-CTSU in Sutton, Surrey. The Team is focused on the molecular classification of tumours, and to decipher the genomic make-up of tumours sensitive and resistance to various treatments using multi-“omics” data. The overall aim is to identify clinically relevant biomarkers to be used as intermediate biological endpoints for phase II trials for targeted therapies. Your work will focus on the development and validation of hypotheses and the generation of molecular markers of breast cancer. An important component of the role will be using tools and software packages that enable reproducible research and develop statistical methods for efficient data analysis. You will assume a key position performing statistical modelling/analysis of in-house (as well as publicly available) next generation sequencing datasets such as Exome, Targeted and Whole genome sequencing, and RNA sequencing datasets, and correlating the results to patient outcome. In addition to a first degree in a subject with strong statistical/mathematical components, the successful applicant will hold a post-graduate qualification in bioinformatics, statistics, computer science, engineering or mathematics. Your analytical experience will enable you to perform integrated analysis. You will also have gained significant experience in bioinformatics role/s, data analysis and related statistical methodologies, have undertaken training and have an interest in clinical trials, genomics or related fields. You will have opportunities to work with cancer biologists, clinicians and computational biologists through our active collaborations so excellent communication and teamwork skills are essential. You should also have the desire and ability to publish and present research at national and international meetings. Additional experience in phosphoproteomic data or kinome activity analyses or in integrated analysis and visualisation of multi-omic datasets would be an advantage. The position will be offered initially on a fixed-term contract of three years, with the potential for renewal thereafter Further information may be obtained by emailing ICR-CTSU at the following address: - ctsu@icr.ac.uk . This email address is for information only. When applying please upload your CV and a supporting statement outlining why you would be suitable for this position including how you meet the person specification and give the names and contact details of two referees. For more details please click on the link for the job description and person specification below. To apply, please click on the Apply button below and follow the instructions. Closing date for applications: 21 October 2018 Interviews to be held week commencing 5 November 2018 We consider all applications on merit and have a strong commitment to enhancing the diversity of our staff. Job Description and Person Specification File upload field, to activate press space bar 512 CancerBiostsatistician_Cheang_Aug 2018.pdf Additional Documentation for Candidates
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