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Third-cycle subject: Computer Science
The scientific work will be conducted in the scope of one of the following projects:
- Interactive semi-situated robot learning: this project addresses the challenge of how to enable robots to learn in a scalable and cost-efficient manner by gradually acquiring new knowledge from a non-expert, semi-situated teachers. To achieve this, computational methods will be developed for robots to query the semi-situated teachers (e.g. crowd workers) and incorporate the newly acquired knowledge into their existing decision-making to further use in situ. This project is funded by the Swedish Foundation for Strategic Research.
- Safe human-robot collaboration: this project aims to explore the relationship between safety and perceived safety in human-robot collaboration. Safe systems may not be necessarily be perceived as safe, whereas unsafe systems might be perceived as safe, depending on their type, form, and structure of the feedback provided to the user. Understanding these tradeoffs is vital to good robot design and acceptance. This project is part of a recently established competence center on Trustworthy Edge Computing Systems and Applications (TECoSA) focusing on research paving the way for novel edge computing systems and applications, emphasizing challenges related to safety, security, and predictability.
Supervision: The doctoral student will be supervised by: Associate Professor Iolanda Leite
To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:
In order to succeed as a doctoral student at KTH, you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:
The candidate must have a degree in Computer Science or related fields. Documented written and spoken English and programming skills are required. Experience with robotics, human-robot interaction, human-computer interaction, and machine learning are important.
After the qualification requirements, great emphasis will be placed on personal qualities and personal suitability.
Target degree: Doctoral degree
Only those admitted to postgraduate education may be employed as a doctoral student. The total length of employment may not be longer than what corresponds to full-time doctoral education in four years ' time. An employed doctoral student can, to a limited extent (maximum 20%), perform certain tasks within their role, e.g. training and administration. A new position as a doctoral student is for a maximum of one year, and then the employment may be renewed for a maximum of two years at a time.
You will find contact information for union representatives on KTH's website.
You will find contact information for the doctoral section on the section's website.
Apply for the position and admission through KTH's recruitment system. It is the applicant’s responsibility to ensure that the application is complete in accordance with the instructions in the advertisement.
Applications must be received at the last closing date at midnight, CET/CEST (Central European Time/central European Summer Time).
Applications must include the following elements:
Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.
For information about the processing of personal data in the recruitment process please read here.
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Disclaimer: In case of a 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 | In agreement with supervisor |
Salary | Monthly salary according to KTH's doctoral student salary agreement |
Number of positions | 2 |
Full-time equivalent | 100% |
City | Stockholm |
County | Stockholms län |
Country | Sweden |
Reference number | J-2020-2452 |
Contact |
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Published | 12.Nov.2020 |
Last application date | 30.Nov.2020 |