Research Associate (wissenschaftlicher Mitarbeiter)
Postdoc Position "Machine Learning for Speech and Audio Processing" (247, DS) E13/E14
The Signal Processing Group is hiring a research associate (wissenschaftlicher Mitarbeiter) "Machine Learning for Speech and Audio Processing". The position is suitable for a postdoctoral researcher. Here is the link to the official job announcement of the Universität Hamburg: link.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Institution: Faculty of Mathematics, Informatics and Natural Sciences, Department of Informatics, Signal Processing (SP)
Salary level: EGR. 13 TV-L / EGR. 14 TV-L
Start date: as soon as possible, fixed for a period of 3 years (This is a fixed-term contract in accordance with Section 2
of the academic fixed-term labor contract act [Wissenschaftszeitvertragsgesetz, WissZeitVG])
Scope of work: full-time position suitable for part-time
Duties primarily include teaching and research. Research associates may also pursue independent research and further academic qualifications.
The general focus of the Signal Processing (SP) research group is on developing novel data science and machine learning methods for processing speech and multimodal signals. Applications include speech communication devices such as hearing aids and voice-controlled assistants. The research associate will do research on novel data science and machine learning methods applied to speech and/or multimodal signals and strengthen our collaboration within the DASHH - Data Science in Hamburg Helmholtz Graduate School. Furthermore the research associate will help establishing degree programs in the data science context.
Typical tasks of a research associate include writing scientific publications, and traveling to conferences and workshops to present the work. The position includes the responsibility to teach 4 hours/week in the computer science department. We are interested in a highly motivated person who is interested in working with us on cutting edge research in a pleasant working atmosphere.
A university degree in a relevant field. An academic degree like a master degree is required, a doctorate is desirable, but not conditional. Examples are Computer Science, Data Science, Machine Learning, and Electrical Engineering. Good knowledge of and experience with modern data science and machine learning techniques is required as well as good programming skills in Python or similar. Knowledge of speech processing and statistics is helpful. Fluent English, spoken and written, and good communication skills are mandatory. Knowledge of German is helpful; we expect the willingness to learn German for non-native
As a University of Excellence, Universität Hamburg is one of the strongest research universities in Germany. As a flagship university in the greater Hamburg region, it nurtures innovative, cooperative contacts to partners within and outside academia. It also provides and promotes sustainable education, knowledge, and knowledge exchange locally, nationally, and internationally. The Free and Hanseatic City of Hamburg promotes equal opportunity. As women are currently underrepresented in this job category at Universität Hamburg according to the evaluation conducted under the Hamburg act on gender equality (Hamburgisches Gleichstellungsgesetz, HambGleiG), we encourage women to apply for this position. Equally qualified and suitable female applicants will receive preference. Qualified disabled candidates or applicants with equivalent status receive preference in the application process.
Tips on applying
Applications should include a cover letter, a tabular curriculum vitae, copies of degree certificate(s) and transcript of grades.
Please send applications by email to: firstname.lastname@example.org in a single PDF-document.
Please start the subject of your E-Mail with [APPLICATION DS] .
Please note that we cannot return application documents. Therefore, do not submit original documents. We will destroy your
documents after the procedure has ended. More information on data protection in selection procedure.