PhD studentship in Machine Learning for Human-Robot Interaction (PI: Frank Foerster, University of Hertfordshire)
Dear all,
on behalf of Frank Förster, I'd like to bring to your notice this PhD opportunity (deadline for applications 30. June 2021):
PhD studentship
MACHINE LEARNING FOR HUMAN-ROBOT INTERACTION
Adaptive Systems Research Group Centre for Computer Science and Informatics Research School of Physics, Engineering and Computer Science University of Hertfordshire, UK Contact: Frank Foerster (f********r@herts.ac.uk)
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Short-listings will start on 30 June 2021* Bursary £15,285 p.a.
* application before this date is strongly encouraged
We invite applications for a PhD studentship at the University of Hertfordshire, UK, under the supervision of Dr. Frank Foerster in the area of robotic language acquisition or symbol grounding as well as approaches to implement repair mechanisms in human-robot interaction more generally. We are particularly interested in pursuing research that connects to the following two topics, but alternative ideas will be considered too.
Research Topics
Topic 1: Socially driven Machine Learning in Robotic Language Acquisition
Topic 2: Repair Mechanisms in Interaction
More information including relevant papers are provided in the following PDF: https://www.herts.ac.uk/__data/assets/pdf_file/0006/331737/ML_HRI.pdf
Independent of the particular topic, we have recently become member of the HomeBank corpora, and would strongly encourage interaction and collaboration with developmental psychologists and psycholinguists.
Person Profile
You will have an excellent first degree and a very keen interest and motivation in human-machine interaction in general or in language acquisition in particular. Optimally you should have an excellent background in Computer Science, Computational/Cognitive Robotics, (computational) linguistics, Artificial intelligence, or similar disciplines with a considerable quantitative/computational component. Due to the interdisciplinary nature of the topic we will also consider applicants with a background in (developmental) psychology, philosophy, or pragmatics as long as you have some experience in programming, machine learning, or dialogue systems. Prior experience with topics such as reinforcement learning, or statistical learning more generally is highly desirable, but not essential if the quantitative background is otherwise very strong. The knowledge of later Wittgenstein is a big plus.
If you have questions, have alternative suggestions for a related, but distinct topic, and/or are generally interested in applying, please contact
Dr. Frank Foerster f********r@herts.ac.uk
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Research in Computer Science at the University of Hertfordshire has been recognised as excellent by the latest Research Assessment Exercise, with 50% of the research submitted being rated as internationally excellent or world leading.
The University of Hertfordshire provides a very stimulating environment, offering a large number of specialised and interdisciplinary seminars as well as general training and researcher development opportunities. The University is situated in Hatfield, in the green belt just north of London. Hatfield is close to Central London (less than 25 minutes by direct train to Kings Cross), with convenient access to Stansted, Luton and Heathrow airports, and, via the nearby historic town of St. Albans, also to Gatwick airport.
Application forms and submission instructions are available under https://www.herts.ac.uk/study/schools-of-study/physics-engineering-and-compu...
Eligibility -----------
Applicants must submit or obtain:
- a completed application form, which can be obtained from website linked above - a research statement stating past experience/research background and interest and motivation/research ambition for current project - two academic references - copies of qualification certificates and transcripts - a copy of your passport
Applications from outside the UK or EU are eligible for this studentship.
The application form should be returned to:
d***********************s@herts.ac.uk
participants (1)
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Daniel Polani