Doctoral student (f/m/d) in the field of machine learning for IoT sensor data – Bremen University of Applied sciences
Bremen University of Applied Sciences is cosmopolitan and promotes science for practice. With around 70 mostly international degree programs and innovative, lifelong forms of study, Bremen University of Applied Sciences offers almost 9,000 students prospects for their personal development and a successful start to their careers. With our international profile, we have held a leading position among universities of applied sciences for decades. The improvement of the study conditions and the attractive design of workplaces are of particular concern to us, which are reflected in the development planning of the university.
At the Bremen University of Applied Sciences, subject to the release of funds, there is a position as of April 1st, 2023 in the Faculty of Electrical Engineering and Computer Science
Doctoral student (f/m/d) in the field of machine learning for IoT sensor data
FOR THE FOCUS PROFESSORSHIP IN THE FIELD OF DIGITAL TRANFORMATION: “DATA SCIENCE”
Reference number: FK4-8-2023, salary group 13 TV-L
with 50% of the weekly working time (19.6 hours), possibly 65% of the weekly working time (25.48 hours), and limited to three years as part of the project “HSB-BestPROfessur: Bremen model for the acquisition and development of professorial staff” . It is a qualification position for the development and implementation of the doctoral project.
- Development of methods for analyzing IoT sensor data, in particular anomaly detection in time series
- Conception and implementation of prototypes in the context of big data applications
- Publication and presentation of research results in specialist journals, at conferences and as part of regional science communication
- Participation in the establishment and further development of scientific networks and cooperation relationships with practice partners
- Assumption of teaching tasks in the amount of 3.5 SWS in the field of data science or in the basic subjects of computer science
- A master’s degree/university diploma in computer science or a comparable subject with an orientation towards IoT data and/or machine learning or comparable with an above-average result
- High degree of motivation, commitment, result orientation and team spirit
- Ability to work independently and on your own responsibility in research
- Analytical view of complex relationships and the ability to think interdisciplinary
- Programming experience and experience in using frameworks for data analysis
- Very good knowledge of spoken and written German and English
- Experience with machine learning methods, especially for time series analysis
- Experiences with industrial IoT applications in the context of Big Data
- An interesting and varied job in an international environment in a cosmopolitan university
- An open working atmosphere
- Flexible working hours at a family-friendly university
- Diverse opportunities for personal and professional development
- A subsidized job ticket for local public transport
- Subsidized company fitness in all qualitrain studios
For university degrees that you completed outside the EU, please submit the German translation and the evaluation of the Central Office for Foreign Education ( ZAB ) . Alternatively, we ask you to send us a PDF excerpt from the database for the recognition and evaluation of foreign educational certificates ( ANABIN ) .
For vocational qualifications that were completed outside of Germany, please send the German translation and the recognition in Germany. Information on this can be found at the Federal Institute for Vocational Training ( BIBB ) .
Bremen University of Applied Sciences promotes the employment of women at all levels. Women are therefore expressly encouraged to apply. Severely disabled applicants will be given priority if they have essentially the same professional and personal suitability. Applications from people with a migration background are welcomed.
Further information on Bremen University of Applied Sciences can be found at www.hs-bremen.de. Prof. Dr.-Ing . Uta Bohnebeck at email@example.com .
We look forward to receiving your meaningful application including documents up to and including April 18, 2023 via career.hs-bremen.de .