Postdoctoral position in Interactive and Interpretable/Explainable Machine Learning for Human-Robot Interaction - Hiring in process/Finished, not possible to apply

The Department of Information Technology has a leading position in research and education. The Department currently has about 300 employees, including 120 teachers and 110 PhD students. More than 4000 students study one or more courses at the department each year. You can find more information about us at the web page of the department of Information Technology

This position is one of four postdoc positions on the topic of equal opportunities aspects in IT.

The position is hosted by the Division of Systems and Control, working closely with members of the Uppsala Social Robotics Lab.The postdoctoral project will be supervised by Katie Winkle (Vi3; Human-Machine Interaction) and David Sumpter (Division of Systems and Control).

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Duties
This postdoctoral project brings together human-robot interaction with interactive and interpretable/explainable machine learning in the context of participatory automation - that is developing robots which can be “taught” by a diverse range of users. This approach aims to create contextually, socially appropriate machine behaviour whilst also delivering on EU Ethics Guidelines for Trustworthy AI.

The main tasks for the postdoc are to:

• Identify, design and implement machine learning system(s) which helps users generate and control the training data from which that system will learn.
• Design and implement visualisations/machine communications that support diverse user understanding of the machine learning process and help identify (e.g. gender) bias within training examples being generated

These systems will be used in projects on “teachable robots” for computing education and expert-taught social robots for health currently being undertaken at the social robotics lab.

The position is focused on the research in the described research project and includes a limited amount of teaching and departmental duties, but no more than 20%.

Requirements
PhD degree in Computer Science, Machine Learning, Robotics, or related areas or a foreign degree equivalent to a PhD degree in Computer Science, Machine Learning, Robotics, or related areas . The degree needs to be obtained by the time of the decision of employment. Those who have obtained a PhD degree three years prior to the application deadline are primarily considered for the employment. The starting point of the three-year frame period is the application deadline. Due to special circumstances, the degree may have been obtained earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc.

Proficiency and demonstrated experience with designing, implementing and evaluating machine learning systems is required. Good communication skills in English, both spoken and written, are required.

Additional qualifications
Experience specifically with interactive machine learning from human demonstrations or explainable machine learning is an advantage, as is experience in working with and implementing robot architectures (i.e. systems consisting of robot(s) plus multiple external input or output devices).

An interest in the social and ethical consequences of AI and robotics would be particularly appreciated.

The application must contain:
A cover letter briefly describing your motivation for applying for this position and project, and indicating the earliest possible employment date (max 1 page). A curriculum vitae (CV). A copy of relevant diplomas and transcripts (translated into Swedish or English). A list of publications. A research statement describing how your past and current research experience can contribute to this project (max 2 pages). Contact information for two references.

About the employment
The employment is a temporary position of 2 years according to central collective agreement. Scope of employment 100 %. Starting date 1 September 2023 or as agreed. Placement: Uppsala

For further information about the position, please contact: Katie Winkle, katie.winkle@it.uu.se or David Sumpter, david.sumpter@it.uu.se, +4618 471 6226.

Please submit your application by 2 May 2023, UFV-PA 2023/972.

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