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Postdoc Position on Bayesian Deep Learning for Audiovisual Speech Recognition

Country : Germany

Website :


At the Cognitive Signal Processing Group, Ruhr-Universität Bochum, Germany, a fully funded postdoc position (100%, funded according to the German public service salary level TVL-E14) is available for a 2-year period starting this summer, with the possibility of extension subject to continued funding.
We are looking for researchers with an excellent PhD in electrical engineering, computer science, physics, or mathematics. Good knowledge of machine learning and a background in Bayesian statistics are important, and knowledge of image processing and excellent English language proficiency are a definite plus. German language skills are not a requirement, but would be helpful. Programming skills in Python and C++ are required, Matlab or Java experience would be an added advantage.
The goal of this work is the development of machine learning strategies under uncertainty in the exciting area of Bayesian deep learning, . These will be applied to the task of highly robust audiovisual large-vocabulary speech recognition, as part of an ongoing project funded by the German research foundation (DFG). In addition to deriving, implementing and evaluating new learning algorithms, you would present the results at international conferences and in journals, publish the most successful algorithms, e.g. via github, and contribute to project reporting.
Ruhr-Universität Bochum supports the career development of women. Applications from women are thus explicitly welcome. In those areas, in which women are underrepresented, they will be considered preferentially according to the regulations of the „Landesgleichstellungsgesetz” if their abilities, aptitude and professional performance are equal with those of the fellow applicants, unless reasons concerning the person of a fellow applicant are predominant. In case of equal qualification, applications of severely disabled persons or persons that are regarded as being on a par with severely disabled persons according to § 2 Abs. 3 SGB IX will be considered preferentially.
Please send applications, containing your CV, Master's transcript, PhD certificate, motivation for applying (max. 1 page), pdf files of two recent publications, and the names of at least two references (email addresses are sufficient) via email to before March 31 for preferential consideration. Position will be open until filled.

Last modified: 2018-02-26 11:30:35