Postgrad LIVE! Study Fairs

Bristol

Nottingham Trent University Featured PhD Programmes
Anglia Ruskin University Featured PhD Programmes
Engineering and Physical Sciences Research Council Featured PhD Programmes
University of Portsmouth Featured PhD Programmes
Birkbeck, University of London Featured PhD Programmes

Data sketching in engineering sensor networks

  • Full or part time
  • Application Deadline
    Sunday, March 31, 2019
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

When analysing data at scale, accurate solutions become computationally cumbersome demanding substantial memory and processing power. In situations where time is critical, e.g. for controlling a process, detecting an anomaly or predicting failure from incoming sensor network data, an approximate answer to the right problem often suffices. To this end, this project will explore how we can analyse such data without resorting to storing an expanding dataset using sketching algorithms based on randomised linear algebra suitable. The intension will be to develop tools for real-time diagnostics using streaming data from avionic or automotive sensors.

Your responsibilities:
• explore ideas, methods and algorithms in statistical inference and randomised linear algebra
• implement algorithms in programming languages (Python, MATLAB)
• present results at international conferences and in scientific publications
• work in a team with other PhD students, postdocs, and staff

Your qualifications:
• Master’s degree (or equivalent) in computational science or scientific computing or similar degree with a focus on applied mathematics and computing
• knowledge/experience in statistical signal processing is an advantage
• interest/experience in applied probability
• programming skills in Python or MATLAB
• fluent in spoken and written English

Our group’s research interests are in computational modelling of physical and engineering systems and inverse problems for imaging, process monitoring, and non-destructive testing. This area entails mathematical modelling, statistical inference and optimisation algorithms. For more info see http://www.homepages.ed.ac.uk/npolydor/

Start date: September 2019.

Funding Notes

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree.

Tuition fees and stipend are available for Home/EU students (International students can apply, but the funding only covers the Home/EU fee rate).

How good is research at University of Edinburgh in General Engineering?
(joint submission with Heriot-Watt University)

FTE Category A staff submitted: 91.80

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully





FindAPhD. Copyright 2005-2019
All rights reserved.