Sketching for data-intensive health analytics

The Real-time Simulation & Computational Imaging Group of the Institute for Digital Communications (IDCOM) at the School of Engineering invites applications for PhD positions on randomised numerical algebra for real-time scientific computing.
 
The aim of the post is to pursue research in the field of randomised numerical algebra for processing streaming biomedical data, e.g. in the context of intensive care monitoring or assisted living. This capability is key to prompt decision and intervention by detecting randomly occurring events (health deterioration, domestic accidents), as well as predicting the likelihood of future events from data trends. From a computational perspective, these tasks translate to online regression and data-driven model learning. The research should produce results in the form of new sampling algorithms that can extract the “most informative” data and their associated analysis to be published in scientific journals and presented at flagship conferences on data science, machine learning and signal processing.
 
The holder of the position should be willing to collaborate with our ACRC (Advanced Care Research Centre) associates and industrial partners. Opportunities to be involved in teaching activities will also be explored if aligned to the career development of the student.
 
Keywords: data sketching, randomised numerical linear algebra, real-time simulation.  
 
Technical queries should be directed to Dr Nick Polydorides (n.polydorides@ed.ac.uk).  

 

Further Information: 

Start date in April-Sept 2021.  Closing date for applications is 28th February 2021, but please apply before 15th January 2021.
 
Funding: We anticipate competitive opportunities for funding to arise in the near future via PhD scholarship schemes.  
 
Further info on the group’s interests and projects http://www.homepages.ed.ac.uk/npolydor/

http://www.homepages.ed.ac.uk/npolydor/PhD2_2021.pdf

Closing Date: 

Sunday, February 28, 2021

Principal Supervisor: 

Eligibility: 

A scientifically oriented person with a First Class or 2.1 Masters/Diploma degree in mathematics or statistics with a focus on inverse problems, statistics and linear algebra. Good programming skills are desirable but non-essential.

Further information on English language requirements for EU/Overseas applicants.

Funding: 

Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere.

Further information and other funding options.