The Machine Learning research lab at the University of Oldenburg is seeking to fill a position for a
Research Associate (m/f/d)
(wissenschaftliche Mitarbeiterin / wissenschaftlicher Mitarbeiter, E13 TV-L, 75 %).
The position can be filled immediately and is funded until 31 March 2023. Depending on the availability of further project funding, an extension can be considered.
The person who fills the position will be part of the Machine Learning group which develops learning and inference algorithms for different types of data. The group is actively involved in a number of projects which aim at developing novel Machine Learning approaches for challenging data. We pursue basic research, develop new technology, and apply our approaches to different tasks such as visual, acoustic and medical data analysis. 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, computer vision, medical diagnostics, and general pattern recognition. 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 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 algorithms for challenging data such as data with few labels, limited amounts of data and/or very noisy data. Novel probabilistic algorithms including deep probabilistic models will be applied and data from medical imaging will be available.
The research work includes and integrates basic Machine Learning research, algorithm development and applications to data from medical imaging. The position is primarily funded by the BMBF in the program Mathematics for Innovation, and is part of a collaborative research project with the University of Bremen and the University of Giessen. The position gives the opportunity to obtain a PhD/doctoral degree.
The appointed researcher will be part of a very dynamic working environment in a research group that represents an expanding new research domain.
For more information about the research group visit http://www.uol.de/ml/.
Applicants have to hold an academic university degree (e.g. Master) in Physics, Mathematics, Computer Science, Electrical Engineering Data Sciences or a closely related subject. Instead of already holding the degree candidates can be close to obtaining their MSc degree (such that they hold the degree when they start the position). Strong analytical/mathematical skills, e.g. as obtained in theoretical/mathematical courses of a Mathematics, Physics or Data Science degree, are required for all candidates. Furthermore, good programming skills (e.g. python, C++, matlab) and prior experience with Machine Learning approaches (ideally probabilistic approaches) are required. Good English language skills are required and German language skills are desirable.
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 case of equal qualification. Applicants with disabilities will be given preference if equally qualified.
Please send your application preferably electronically (PDF) to Jörg Lücke firstname.lastname@example.org or per mail to Carl von Ossietzky Universität Oldenburg, Fakultät VI, Machine Learning, z. Hd. Prof. Jörg Lücke, 26111 Oldenburg, Germany. The application documents should contain: a short cover letter stating why you are interested in the position (half a page), a CV, transcripts of BSc and MSc degrees (or a preliminary transcript if applicable), publications if applicable, and one recommendation letter. Furthermore, please state the contact details of two of your past/current advisors (one advisor can be the same person who has written the letter). Please use "Application Research Associate Position" as subject line.
Please send your application until 19 July 2020.