Research Associate in Statistical Machine Learning
Imperial College London - Department of Medicine
|Salary:||£36,070 to £43,350 per annum|
|Contract Type:||Contract / Temporary|
|Placed on:||17th October 2016|
|Closes:||14th November 2016|
South Kensington/St Mary’s Campus
An exciting opportunity has arisen for a postdoctoral Research Associate in the Section of Paediatrics within the Division of Infectious Diseases, Department of Medicine at Imperial College London.
You will join a multidisciplinary research team led by Professor Adnan Custovic, centered on implementing and developing statistical machine learning models to understand the progression of asthma and allergic diseases from childhood to adulthood.
The selected candidate will work as part of the Wellcome Trust strategic grant entitled “Pulmonary epithelial barrier and immunological functions at birth and in early life - key determinants of the development of asthma?”. The aim of this project is to implement and potentially develop innovative computational statistical methods to identify novel subtypes of childhood asthma, enabling investigation of subtype-specific environmental and genetic associates and discovery of distinct pathophysiological mechanism.
You must have a PhD or equivalent in Statistics, Data Science, Machine Learning or a related field. Successful candidates should have a high level of expertise in one or more of the following areas: quantitative research methods, dimensionality reduction techniques, Bayesian data analysis, multilevel modelling, latent variable modelling and/or longitudinal analyses of cohort data. In addition, candidates should have strong data management skills and a high degree of proficiency with one or more statistical software packages (e.g., SAS, STATA, R/SPLUS, MPLUS, PLINK, Python, C).
This is a full-time, fixed term post until 18 March 2019, based at the South Kensington and St Mary’s Campuses.
Our preferred method of application is online via our website at http://www3.imperial.ac.uk/employment (please select “Job Search” then enter the job title or vacancy reference number into “Keywords”). Please complete and upload an application form as directed quoting reference number HM2016201.
Alternatively, if you are unable to apply online, please email email@example.com to request an application form.
Closing Date: 14 November 2016 (Midnight GMT)
Committed to equality and valuing diversity. We are also an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Disability Confident Employer and are working in partnership with GIRES to promote respect for trans people.
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