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Assistant Professorship of Computer Science (Tenure Track)

Published 20 July 2018 (217 days ago)
Deadline for applications 29 August 2018 (177 days ago)
Full-time position
University of Innsbruck Innsbruck (Österreich)
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Position of Assistant Professor (with Tenure-Track Option) of Computer Science in
Embodied Artificial Intelligence and Machine Learning

The Department of Computer Science (at the Faculty of Mathematics, Computer Science and Physics) at the University of Innsbruck seeks to fill the position of a full-time

Assistant Professor of Computer Science
in the area of Embodied Artificial Intelligence and Machine Learning

as of October 1, 2018. This position is initially limited to 6 years; a tenure-track agreement can be offered within the first year of employment. Upon positive evaluation the position is converted into a tenured Associate Professorship.

This career position is embedded in an attractive environment of existing competencies close to the above thematic area, including Autonomous Robotics, Machine Learning, Computer Vision, Data Science, Recommender Systems, Compressed Sensing, and Dictionary Learning. Moreover, this is one of 12 career positions the University of Innsbruck is creating in diverse scientific disciplines connected to digitalization; the Development Plan 2019-2024 of the University of Innsbruck includes the creation of a new, interdisciplinary center for digitalization.

Tasks
The successful applicant should engage in topics within the area of Embodied Artificial Intelligence and Machine Learning in research and teaching.

Embodied Artificial Intelligence refers to Artificial Intelligence (AI) in the widest sense with particular focus on interaction with the physical world by means of sensors and/or actuators. Embodied Artificial Intelligence aims to increase autonomy, flexibility, fault tolerance, and the ability of artificial systems to communicate within our world.

Specific topics of interest may include for example:
  • Autonomous robots or vehicles capable of learning;
  • Autonomous, exploratory and/or guided learning in open scenarios;
  • Incremental/hierarchical learning of reusable and composable concepts;
  • Learning and planning across continuous (sensors, actuators) and discrete (symbolic) representations.
Teaching comprises lectures especially in the above area in the study programs of the Department of Computer Science, including mandatory courses in the bachelor program. In addition, co-supervision of Bachelor, Master and PhD theses is expected.

Participation in the academic self-management is a matter of course.

Eligibility Requirements
  1. Doctoral degree in computer science or a related field;
  2. Postdoctoral experience;
  3. Pertinent scientific achievements beyond the dissertation/PhD thesis;
  4. Research experience in the area of embodied AI and machine learning;
  5. Relevant publications in leading international, refereed journals, and presentations at international conferences/workshops;
  6. International experience;
  7. Experience in the acquisition and/or scientific management of research projects;
  8. Excellent written and oral communication skills in English;
  9. Team and communication skills.
How to Apply
The application must be submitted in English and must contain a CV with a description of the academic and professional career, a list of scientific publications, presentations, projects, and other scientific work performed, as well as names and contact information of at least two references. The application must also include a teaching concept and a research concept.

The University of Innsbruck strives to increase the proportion of its female employees, especially in leadership positions, and therefore explicitly invites women to apply. In the case of equivalent qualifications, female applicants will be given preference.

We look forward to receiving your online application (Chiffre MIP 10040) until 29.08.2018 at
https://orawww.uibk.ac.at/public/karriereportal.home

The legally-binding text in German may be found at:
https://orawww.uibk.ac.at/public/karriereportal.details?asg_id_in=10040
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Published on academics.com on 20 July 2018

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