PhD Studentship in Machine Learning, Physiological and Affective Computing

PhD studentship available at UCL Computer Science in 2020

Call: talented students are invited to propose a PhD research project in areas related to machine learning, physiological and affective computing, with the aim to create novel assistive technology and boost disability innovation.

* You can also apply for the project described below.

Project Title
Mobile thermography-based cardiovascular and cortical imaging for detecting anxiety in hospitalised children

The decreasing cost and size of thermal imagining technology opens new possibilities for monitoring physiological anxiety-related indicators. This PhD project addresses the computational challenges of tracking and extracting physiological indicators in static and ubiquitous settings from thermal imaging of children’s face and scalp. Anxiety is a major issue for many children including children with mental disability and hospitalised children with long-term illness. It undermines therapies, causes psychological trauma and may cause life-long morbidity.

The project will aim to: 1) develop novel algorithms that enable and significantly decrease the computational cost for thermal imaging-based cardiovascular measurements related to anxiety, 2) achieve a robustness against noises in statistical parametrical mapping for thermal cortical imaging, 3) develop machine learning techniques for detecting anxiety-related cardiovascular and cortical thermal signatures, and 4) investigate the above challenges in the setting of the children hospital life.

Two experimental settings will be used: a) lab studies where anxiety will be manipulated by using widely-used anxiety-induction methods with adult participants, b) real-world clinical studies in collaboration with Great Ormond Street Hospital; we will explore the use of such thermal imagining technology to screen for anxiety with a view to therapeutic interventions, prior to and in preparation for clinical operative procedures.

Applications for 2020-21 are now being accepted

Person Specification

Applicants should be interested in Physiological Computing, Artificial Intelligence, Human-Computer Interaction and Assistive Technology.
Applicants should possess a Masters degree in a related discipline. Prospective candidates should also have an interest and experience in some of these areas: Computer Vision, Machine Learning, Physiological Signal Processing, Brain Imaging or Brain-Computer Interface.

Application Procedure

1st Round: expressing your interest by emailing to “youngjun[dot]cho[at]” with the items below

  1. a copy of CV
  2. Brief personal statement
  3. Brief research proposal (1page)

2nd Round: making a full application

Applicants should submit their applications via UCL Select
NB: Please indicate clearly on your application that you are applying for this Scholarship (“Physiological Computing“) under the supervision of (“Dr. Youngjun Cho“).
Also, please notify Aeesha Adams with your application number when you apply. Applications must include:

  1. Contact details of applicant
  2. A personal statement and separate research proposal (2 – 5 pages) describing the research question, a summary of some relevant literature, and an outline of the type of research to be conducted (including ideas about which methods would be appropriate).
  3. Name and email contact details of 2 referees
  4. Academic transcripts
  5. A CV