Research Associate at the Machine Learning research group

Страна: Германия;

Дедлайн: 08.10.2015



The Machine Learning research group at the University of Oldenburg is seeking to fill a position for a

Research Associate
(wissenschaftliche Mitarbeiterin / wissenschaftlicher Mitarbeiter, E13 TV-L, 75%).

The PhD position is part of the Machine Learning group which develops learning and inference technology for sensory data. The group is part of the Cluster of Excellence Hearing4all and the Department of Medical Physics and Acoustics within the School of Medicine and Health Sciences. We pursue basic research, develop new technology, and apply our approaches to different tasks with a focus on acoustic and visual data. Our research combines modern probabilistic approaches, modern computer technology and insights from the neurosciences. We develop novel methods and improve existing methods for computer hearing, pattern recognition and computer vision. Furthermore, we model biological information processing and use the obtained insights to contribute to the development of artificial intelligence. Research will be conducted in close collaboration with leading international and national research labs. Our Machine Learning research can be considered as part of the Data Sciences, Computational Sciences, or Big Data approaches.

The research focus of the position will be on the development of new probabilistic learning algorithms, their theoretical foundations, and/or their applications to high-dimensional sensory data. The project will emphasize basic research for general purpose learning and pattern recognition in connection with applications to specific tasks (acoustic and other data).

At the starting time of the position applicants have to hold an academic university degree (e.g. Master) in Physics, Computer Science, Mathematics, Electrical Engineering or a closely related subject. Strong analytical/mathematical skills, e.g. as obtained in theoretical/mathematical courses of a Physics degree, are required for all candidates. Furthermore, very good programming skills (e.g. python, matlab, C++) are required. Prior experiences with Machine Learning approaches and sensory data processing are a plus but are not strictly required. Very good English language skills are required and German language skills are desirable. The position can be filled immediately and is available for two years with the intention of a further extension.

The appointed researcher will be part of a new working environment. The research group has been established in the past year and is currently extended. The group is located in a new building, and the Cluster of Excellence Hearing4all is part of the German Excellence Initiative which funds top-tier research in Germany. Numerous established and new research groups within the Cluster and the University provide an attractive scientific and social environment.

For more information about the research group visit

For more information about the Cluster of Excellence Hearing4all visit

The University of Oldenburg is dedicated to increasing the percentage of women in science. Therefore, female candidates are particularly encouraged to apply. According to § 21 III NHG (legislation governing Higher Education in Lower Saxony) preference will be given to female candidates in cases of equal qualification. Handicapped applicants will be given preference if equally qualified.

Please send your application preferably electronically (PDF) to Jörg Lücke <> or per mail to: Carl von Ossietzky Universität Oldenburg, Fakultät VI, Machine Learning, z. Hd. Frau Jennifer Köllner, 26111 Oldenburg, Germany. The application documents should contain: a short cover letter stating why you are interested in the position, a CV, transcripts of BSc and MSc degrees (a preliminary transcript if applicable), publications if applicable, and two recommendation letters or contact details of two of your past/current advisors). Please use “Research Associate Position, Machine Learning” as subject line.

Please send your application until 8 October 2015.