Research Associate

Imperial College London - Myocardial Function, National Heart and Lung Institute & Data Science Institute 

Applications are invited for the position of Research Associate, to work in the Myocardial Function Group as part of the ElectroCardioMaths Group.

We are seeking a highly motivated scientist to join a collaborative team of clinicians, basic scientists, and mathematicians/engineers interested in cardiac electrophysiology. The project will use unsupervised learning techniques to investigate novel classifiers and characteristics of electrogram morphology with the aim of improving clinical diagnosis and our understanding of cardiac arrhythmias.  You will be expected to analyse atrial electrograms, identify appropriate machine learning algorithms and apply them, with a gradual increase in responsibility and autonomy in the design and overall strategy, and in the management of internal and external collaborations.

You should have a PhD in Computer Science or Statistics, and have expertise in using machine learning techniques, such as recurrent neural networks or manifold learning, to solve practical problem in either engineering, clinical or commercial problems, especially in relation to time-series analysis. A background in cardiac electrophysiology research is desirable. The post will require collaboration with other groups both within and outside the department.

The post is full-time fixed-term for 24 months and will be primarily based at the Hammersmith Campus, located in East Acton. The post-holder will also be expected to work at, and interact with, the Data Science Institute at the South Kensington Campus.

Further information on the group's work can be found at:

https://www1.imperial.ac.uk/nhli/cardio/myocardial_function/electro/electrocardiomaths/

Informal enquiries may be sent to Dr Chris Cantwell (c.cantwell@imperial.ac.uk)

Our preferred method of application is online via our website 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.

Alternatively, if you are unable to apply online, please email rb.recruitment@imperial.ac.uk to request an application form.                                                                                         

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