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We are seeking a Postdoc for the project “Prediction and Coordination for Conversational AI”, led by Prof. Gabriel Skantze at KTH Royal Institute of Technology in Stockholm, Sweden. The project is part of our larger goal of developing systems, such as social robots, that can engage in spoken interaction with humans in the same natural way we interact with each other. In the project we use data of spoken interaction between humans and explore models that can make predictions about the speakers’ future behavior, including what they will say and when they will speak. These models will then be used to allow a conversational agent to anticipate the human partner’s actions and adapt accordingly, in order to improve coordination, such as smooth turn-taking. An important aspect of the project is also to analyze these models to gain better understanding of how communicative signals enable prediction and coordination in conversation.
The work builds upon our previous and ongoing work around the development of such models using self-supervised learning (e.g., Skantze 2017, Roddy et al 2018, Ekstedt & Skantze 2020), and you will work together with a PhD student already working in the project. The modelling involves several modalities, including speech, text and gaze, and it is therefore advantageous if you have experience of methods from both speech technology and NLP. The project is highly interdisciplinary, and we would like to see applicants with interests in both machine learning, linguistics, and psychology.
The work will take place in the speech group at the department of Speech Music and Hearing, at KTH – an internationally recognized research lab in speech and language technology. The research at the department is focused on human-like communication with machines and robots based on multimodal information. This research area is truly multi-disciplinary, bridging computer science, machine learning, linguistics, and perception and cognitive disciplines. For more information, see https://www.kth.se/en/csc/forskning/tmh
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Requirements
Applicants should have a PhD degree in a subject relevant for the research, such as computer science, speech technology, computational linguistics, or cognitive science. The position requires good skills in programming, machine learning, and statistical analysis. Good command of English, in writing and speaking, is a prerequisite for presenting research results in international periodicals and at conferences. We also expect applicants to have a deep interest in spoken language interaction, and to have done their PhD in a related area.
Preferred qualifications
Candidates with interdisciplinary backgrounds are especially welcome to apply. We would like to see that you have experience of formulating research ideas independently from your supervisor and getting them implemented. At the same time, experience of doing research in collaboration with others is commendable. You should also be aware of diversity and equal opportunity issues.
Great emphasis will be placed on personal competency.
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The application must include:
Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).
The position offered is for, at the most, two years.
A position as a postdoctoral fellow is a time-limited qualified appointment focusing mainly on research, intended as a first career step after a dissertation.
Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.
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Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.
Type of employment | Temporary position |
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Contract type | Full time |
First day of employment | As agreed |
Salary | Monthly salary |
Number of positions | 1 |
Full-time equivalent | 100% |
City | Stockholm |
County | Stockholms län |
Country | Sweden |
Reference number | J-2020-2807 |
Contact |
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Published | 11.Dec.2020 |
Last application date | 29.Jan.2021 11:59 PM CET |