Marie Curie Fellowship in Machine Learning / Bioinformatics

Job Location
Pharmatics Limited
9 Little France Road
EH16 4UX
United Kingdom
~£52,110 (UK STERLINGs)

An additional mobility allowance of £7,400-£10,495 p.a.

Job Description

Applications are invited for a fellowship in machine learning for personalized medicine, to be funded by the Marie Curie Initial Training Network MLPM2012 of the 7th Framework Programme of the European Commission. MLPM ( is a consortium of several universities, research institutions and companies located in Belgium, France, Germany, the Netherlands, Spain, Switzerland, UK, and in the USA. MLPM offers an excellent training environment in the research field at the intersection of machine learning and medicine. It includes several academic labs with expertise in statistical genetics or machine learning, and private companies that are active in this field. The recruited fellow will be based at award-winning start-up company Pharmatics in Edinburgh, UK. The fellow will visit other nodes and attend training events of the network, in particular the annual summer schools on Machine Learning for Personalized Medicine. The immediately available position is fully funded (100% employment) until 31/12/2016 according to the Marie Curie programme, which offers a highly competitive and attractive salary.

Research project: The recruited fellow will develop novel machine learning / bioinformatics methods for predictions of complex disease-related phenotypes, disease subtyping, and patient stratification based on heterogeneous high-dimensional molecular measurements and clinical/environmental variables. The methods may be extended to longitudinal (time series) phenotypes. Effects of possible shifts between training and test distributions will be considered. The methods will be investigated for several clinical datasets and build on the current understanding of targeted clinical indications. If the new methods outperform current clinical models for stratification and prediction of diseases and related outcomes, they may be investigated further in prospective clinical studies and eventually packaged as medical devices.


Successful candidates will have a PhD or more than 4 full-time years of research experience in machine learning, bioinformatics, statistical genetics, epidemiology, or related disciplines at the time of recruitment. To be eligible under FP7 ITN rules, they must have no more than 5 full-time years of research experience, and must not have resided, worked, or studied in the country of their host organization (UK) for more than 12 months in the 3 years prior to the time of recruitment. The years of experience are measured from the time when the candidates obtained a degree that would entitle them to formally embark on a doctorate. Proficiency with R, Matlab, and/or Python is required. The successful candidate will have strong familiarity with at least three of: sparse predictive methods, kernel methods, ensemble methods, transfer learning, network modelling, semi-supervised learning, patient stratification, in vitro diagnostics, statistical genetics, molecular biology, molecular pathology, clinical trials, epidemiology.

About Our Organization

Pharmatics is an award-winning start-up company developing machine learning-based products for preclinical and clinical studies, and has expertise in machine learning, statistical genetics, molecular epidemiology, clinical trials, and a range of diseases and indications. Pharmatics is actively involved in biomarker studies of rheumatoid arthritis, cardiovascular diseases, and complications of diabetes

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