SICSA continues to grow as a world-class pool of researchers in Informatics and Computing Science and there are a range of vacancies occurring regularly across the SICSA member Universities.
This page also features vacancies from industrial employers seeking to recruit graduates in Informatics and Computing Science. Please note that all applications to external vacancies (outside SICSA) must be made directly to the advertising institution or organisation and not via SICSA.
PhD in Computing Science: Actionable Information Finding from Crisis Big Data through Structured Collaboration between AIs and Volunteers
University of Glasgow
Start Date: 1 October 2019
Funding is available to cover tuition fees for UK/EU applicants for 3 years, as well as paying a stipend at the Research Council rate (estimated £15,009 for Session 2019-20)
The Glasgow Information Retrieval group is looking for motivated students interested in our doctoral program. We are looking for a PhD student to work on emerging machine learning challenges in the emergency management domain to support response efforts during natural disasters (e.g. flooding, earthquakes or hurricanes). A successful student taking this opportunity will work with both public reports from first responders as well as high volume of social media data, working to improve the situational awareness of response personnel in the command and control centre during disasters.
The broad aim of this PhD programme is to examine and extend state-of-the-art active learning and artificial intelligence algorithms (e.g. new neural network architectures) when integrated with volunteering efforts (crowdsourcing), with the goal of identifying and cross-referencing actionable information from social media with on-going response activities. This will involve learning about how machine learning algorithms evolve over time and can be directed/tuned through human input, as well as learning about emergency response working practices and what makes information valuable during emergency situations.
Environment: The successful candidate will enrol as a PhD student at the School of Computing Science (Information, Data, Analysis Section), University of Glasgow, under the supervision of Dr Richard McCreadie. The successful candidate will be based in the Glasgow Information Retrieval Group, and will be expected to collaborate with experts in Big Data processing, Machine Learning from across the IDA Section. The successful candidate will have access to a state-of-the-art cluster of machines, including a cluster of new GPU servers, as well as terabytes of historical social media data.
Skills: The ideal candidate will have a strong background in Computer Science and some background in Statistics. In particular, the student is expected to have strong programming skills, some prior experience of machine learning and/or crowdsourcing, a good command of English and team working skills.
Eligibility: Full funding is provided for EU/UK students (standard home/EU fees and stipend rates included). Non-EU/UK students can apply, however they would be required to pay the difference between the home/EU and international fee.
Contact Information: For further information, interested candidates can contact Richard McCreadie (firstname.lastname@example.org)
Excellence bursaries for postgraduate research at the University of Glasgow
The School of Computing Science is delighted to announce the introduction of several international and home/EU excellence bursaries for postgraduate research students.
These new bursaries are designed to attract talented students to join our world leading Research sections, working on new and challenging problems in computer science. These are fee scholarships, hence the value of the bursary will be reduced from the tuition fee payable to the University.
These bursaries are open to both home/EU and international applicants.
For more information on this opportunity and application details please visit: https://www.gla.ac.uk/schools/computing/postgraduateresearch/excellencebursaries/
Deadline is 16th August 2019