Postdoc: Machine Learning and the Analysis of Medical Sensor Data (Edinburgh, UK)
Applications are invited for an experienced researcher to develop and validate advanced statistical methods for the analysis of data from a novel multiplexed sensor in the lungs and blood vessels. The post is part of a large Interdisciplinary Research Collaboration which
involves: the development of novel chemical sensors and detectors; the development of inference methods to analyse the data produced and infer the concentration of various pathological processes present so as to provide doctors with information on the state of intensive care unit patients; and the testing of the methods in in-vitro, ex-vivo and in-vivo assay systems. The post will be supervised by Professor Chris Williams, School of Informatics, University of Edinburgh.
The successful candidate will be a probabilistic machine-learning researcher (or similar) keen to work on a challenging application area. The data will come from two sources: (i) spectral data (from surface-enhanced Raman spectroscopy, SERS), and (ii) imaging data from the lungs. These data will be used to infer the concentration of various pathogens present. The integration of information collected from different sources will be tackled using hierarchical Bayesian models. Over the duration of the project the richness and complexity the sensed data and the number of spectral signals will increase.
You will be self-motivated with the ability to take day-to-day responsibility for the progress of the proposed work and collaborate effectively with project partners from medicine, physics, chemistry and engineering. There is potential for innovative methodological developments in the modelling framework. The post offers the opportunity to work in a world-class machine-learning research environment, applying and extending cutting edge methods in an important application area.
This is initially a fixed term contract for 2 years. Dependent on the results of a mid-term review of the programme by EPSRC, the post may be extended for a further 2 years.
This is a readvertisement and previous applicants need not apply.
Vacancy Ref: : 028993
Closing Date : 12 May 2014
Salary: GBP 30,728 - 36,661
To apply: https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.j...
Informal enquiries: Professor Chris Williams: ckiw(at)inf.ed.ac.uk.