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Position: Ph.D. Student Position
Institution: Johannes Kepler Universität Linz
Department: Department of Knowledge-Based Mathematical Systems
Location: Linz, Oberösterreich, Austria
Duties: Develop new methods and algorithms for integrating human feedback into evolving fuzzy models; Integrate components into the interactive framework on methodological and software-technical level in collaboration with the post-doc; Evaluate and test based on real-world data; Complete a doctoral dissertation towards the end of the project; Work together with the project leader and the post-doc
Requirements: The successful candidate must hold a Master’s degree in Computer Science and/or Mechatronics and/or Mathematics (minimal ECTS points received: 300); Skills in machine learning, ideally with expertise in fuzzy systems design and data-stream modeling; Professional experience in programming, especially within MATLAB environment; Professional experience in writing publications and conducting research as well as in developing own algorithms; Fluency in spoken and written English
   
Text: As the largest institution of research and education in Upper Austria, the Johannes Kepler University Linz has over 20,000 enrolled students and 3,300 employees. The JKU’s four faculties offer over 70 academic degree programs. We are looking to strengthen our team at the Faculty of Engineering and Natural Sciences and announce a job opening starting March 1, 2020, for a Ph.D. Student Position for a 30-hour/week, three-year position at the Department of Knowledge-Based Mathematical Systems Job Reference Number: 4001 The position will be held within a basic research project (financed by the FWF), where the major focus lies on the design of an interactive machine learning framework with the usage of evolving fuzzy systems methodology. The framework should operate in on-line mode and be able to cope with (measurement) data and expert input likewise, in order to stimulate “humans-in-the-loop” in on-line learning systems and thus to increase their transparency, consistency and performance. Job Duties:  Develop new methods and algorithms for integrating human feedback into evolving fuzzy models  Integrate components into the interactive framework on methodological and software-technical level in collaboration with the post-doc  Evaluate and test based on real-world data  Complete a doctoral dissertation towards the end of the project  Work together with the project leader and the post-doc Your Qualifications:  The successful candidate must hold a Master’s degree in Computer Science and/or Mechatronics and/or Mathematics (minimal ECTS points received: 300)  Skills in machine learning, ideally with expertise in fuzzy systems design and data-stream modeling  Professional experience in programming, especially within MATLAB environment  Professional experience in writing publications and conducting research as well as in developing own algorithms  Fluency in spoken and written English The minimum salary based on the FWF’s personnel costs is € 2,162.40 gross per month (14 x per year) for a 30-hour/week position. If you have questions, please contact: Dr. Edwin Lughofer, P +43 7236 3343 431, E-mail: edwin.lughofer@jku.at. Application deadline: November 15, 2019. The Johannes Kepler University wishes to increase the proportion of academic female faculty and, for this reason, especially welcomes applications by qualified women. If applicants are equally qualified, a woman will be given preference for this position. The university welcomes applications from qualified applicants with physical disabilities. These applications will be given special consideration. Prospective applicants interested in the multifaceted position are requested to electronically send an application in adherence to the stated criteria together with the requested documentation (especially a detailed CV) via mail to edwin.lughofer@jku.at.
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