Generative Deep Neural Networks for Interaction with Autonomous Systems (VERSO)
The goal of VERSO is to investigate data-driven, machine learning techniques for communicating with autonomous systems through natural language interaction, where the user can interrogate the system with regards its autonomous behaviour and the data it has collected. The ultimate goal is to increase user trust and confidence in such autonomous systems.
The preferred candidate will have good technical skills with strengths in computer programming and machine learning, and a strong interest in interactive systems, natural language processing and /or generation. The candidate will be expected to have (or expect to gain) a 1st-class honours degree in computer science, or at least a 2nd-class honours degree and a MSc degree in computer science (or related subject area). The student would ideally begin their studies in September 2017.
The position will be funded for three years and includes payment of fees (up to EU level) and a non-taxable stipend of around £16,000 per annum. Overseas students would be required to pay the fee difference from EU level.
The position is co-funded by The Data Lab and SeeByte Ltd through the Data Lab’s Collaborative PhD & EngD Projects programme. The student will spend part of their time at Heriot-Watt University, and part at the SeeByte offices, for the duration of their studies.
Supervision: This position is jointly supervised by Dr. Helen Hastie from the Interaction Lab in the School of Mathematical and Computer Sciences (MACS) and Prof. Yvan Petillot from the School of Engineering and Physical Sciences: Sensors, Signals & Systems at Heriot Watt University.
How to apply: Closing date June 26th
To apply for this position, please complete the application form . When completing the application form, be sure to specify “Dr. Helen Hastie” as the project supervisor, and specify “Data Lab funded” as the source of funding. Applicants are requested to send an email to Dr. Helen Hastie once they have submitted their application.
For further information regarding this position please email Helen Hastie.