PhD Studentship: Deep Learning for Mobile Camera Networks

Queen Mary University of London - School of Electronic Engineering and Computer Science

The Centre for Intelligent Sensing at Queen Mary University of London invites applications for a PhD Studentship to undertake research in the area of machine learning and mobile computer vision for scene monitoring with multiple collaborative robotic or wearable cameras. The PhD project will focus on machine learning methods for people detection and tracking, scene analysis, and activity recognition for assistive technologies.

All nationalities are eligible to apply for this studentship, to be started in or after June 2017. The studentship is for up to four years, and covers student fees as well as a tax-free stipend.

This PhD project is part of an interdisciplinary collaboration between the Centre for Intelligent Sensing (http://cis.eecs.qmul.ac.uk) at Queen Mary University of London (QMUL) and the Centre for Information Technology (http://ict.fbk.eu) at the Fondazione Bruno Kessler (FBK), Trento, Italy. The PhD student will spend approximatively half of their time in London and half of their PhD time in Trento and will have access to state-of-the-art laboratories, including aerial and ground robotic sensors, a multi-camera installation at a large open hallway, and a smart home facility equipped with multiple cameras. The PhD student will be based at Centre for Intelligent Sensing in the School of Electronic Engineering and Computer Science at Queen Mary, University of London and will be supervised by Professor Andrea Cavallaro and Dr Oswald Lanz.

Candidates should have a first-class honours degree or equivalent, or a good MSc Degree, in Computer Science, Physics, Mathematics, or Electronic Engineering. Candidates must be confident in applied mathematics, and should have good programming experience, in particular of C/C++ language and of MATLAB environment. Previous knowledge of Robotic Vision or Distributed Signal Processing or Deep Learning/Machine Learning is required.

To apply please follow the on-line process accessed via the 'apply' link below, selecting Electronic Engineering or Computer Science in the A-Z list of research opportunities and following the instructions on the right hand side of the web page. Please note that instead of the 'Research Proposal' we request a 'Statement of Research Interests'. Your Statement of Research Interest (no more than 500 words or one side of A4 paper) should state whether you are interested in a computer vision PhD project, or an audio processing PhD project, or an audio-visual processing PhD project. Moreover, your Statement of Research Interest should answer two questions:

  • Why are you interested in the proposed area?
  • What is your experience in the proposed area?

In addition we would also like you to send a sample of your written work. This might be a chapter of your final year dissertation, or a published conference or journal paper.

For more information and to apply, please visit: http://www.eecs.qmul.ac.uk/phd/apply.php.

Informal enquiries can be made by email to Professor Andrea Cavallaro (a.cavallaro@qmul.ac.uk).

The closing date for the applications is 15 May 2017.

Interviews are expected to take place during the week commencing 22 May 2017.

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Type / Role:

PhD

Location(s):

London