Salary upto £43468pa plus excellent benefits
Fixed-term until 31st August 2019
We are seeking an expert Data Scientist to work on mining and modelling pathogen phenotypic, genomic and epidemiological data for the identification and surveillance of risk patterns. You will work with a team of software engineers, genomic epidemiologists and microbial genomic researchers based at The Centre for Genomic Pathogen Surveillance (CGPS) and lead the utility and application of ML and data analytic methods across our project workspaces.
The role is part of a NIH grant on ‘Big Data for knowledge’ and is a collaboration between the Centre for Genomic Pathogen Surveillance at the Wellcome Sanger Institute and the WHO Collaborating Centre for surveillance of antimicrobial resistance, Boston, USA.
Our partner on this project, the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance, has been responsible for the development of a widely used software called WHONET (120 countries, over 10,000 labs), which allows laboratories to collate microbiological and phenotypic data on isolates (samples from patients), including whether they are resistant or sensitive to sets of antimicrobials.
Your role will be to help develop analytic frameworks for data collated from a large number of WHONET instances (and similar platforms) to develop intelligent alerting for flagging the emergence of risk and the subsequent intelligent use of Whole Genome Sequencing (WGS) (eg for risk flagging, diagnostics and inference of transmission).
You should have expertise in one or more of data mining, statistical analysis, machine learning and modelling and a thirst for utilising your expertise to provide methods for use in real world applications. The post will involve substantial liaison with local and international agencies and partners in Low and Middle Income Countries (LMICs) focussed on the generation of and intelligent use of surveillance data for the control of AMR.
Essential Skills Advanced degree in Computing, Mathematics, Statistics or similar numerical discipline Strong programming skills (including statistical modelling eg Python or R). Experience using machine learning algorithms. Demonstrable quantitative, qualitative research and analytics experience. The ability to come up with solutions to loosely defined analytic problems by using pattern detection over potentially large datasets. Desire and ability to work with other quantitative and information disciplines to explore where Data Science and ML can complement existing work and help drive surveillance of AMR in the future. A high level of interpersonal skills to be able to elicit complex requirements from, and convey complex requirements to, groups with differing technical backgrounds. Ability to prioritise tasks, organise work effectively and crucially, work as part of a team. Ability to present and give positive input and discussion at meetings.
Other information For the surveillance of AMR, hospitals and labs routinely test microbial samples against a range of antimicrobial agents and often store this information in data management systems. Increasingly, whole genome sequencing (WGS) is used to sequence the genome of corresponding isolates which enables correlation of presence/absence of genes (or mutations) with the laboratory tests. The delivery of analytic outputs and the development of models to learn, improve our understanding and deliver information to decision makers (eg at hospitals and national labs) offer exciting potential to enhance the control and spread of pathogens of high risk to human and animal health. The development of algorithms, statistical learning and the translation of these methods into operational real-time analytical code and web applications will enable the delivery of data for action. The Wellcome Sanger Institute is a charitably funded research centre and committed to training the next generation of genome scientists. Focused on understanding the role of genetics in health and disease and a world leader in the genomic revolution, our mission is to use genome sequences to advance understanding of human and pathogen biology in order to improve human health. We aim to provide results that can be translated into diagnostics, treatments or therapies that reduce global health burdens. Our science is large-scale and organised into Programmes, led by our Faculty who conceive and deliver our science, and supported by our Scientific Operations teams responsible for all data production pipelines at the Institute. Our Campus: Set over 125 acres, the stunning and dynamic Wellcome Genome Campus is the biggest aggregate concentration of people in the world working on the common theme of Genomes and BioData. It brings together a diverse and extraordinary scientific community, committed to delivering life-changing science with the reach, scale and imagination to solve some of humanity’s greatest challenges. Genome Research Limited is an Equal Opportunity employer. As part of our commitment to gender equality and promoting women’s careers in science, we hold an Athena SWAN Bronze Award. We will consider all applicants without discrimination on grounds of disability, sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law.
Please include a covering letter and CV with your application.
Closing date: 12th April 2018