Research Assistaant in Anonymisation of Mobility Data (AnoMoB) Hochschule Esslingen

Within the funding guideline for a "Research Network for the Secure Use of Data" the German Ministry of Education and Research (BMBF) is funding the research project "Anonymous Collection and Use of Mobility Data" (AnoMoB). The project aims to develop technical solutions to collect mobility data securely from mobility users with minimal impact on the users’ privacy and to anonymize the sensitive mobility data for further use. Cryptographic secure computation methods will be used for the secure collection of data while the anonymization will employ methods from machine learning. The research project is carried out in cooperation with several companies from the mobility sector and a non-university research institute. BMBF project profile (in German): https://www.forschung-it-sicherheit-kommunikationssysteme.de/projekte/anomob Esslingen University of Applied Sciences is looking for a research assistant for the project "Anonymisation of Mobility Data (AnoMoB)" at the Faculty of Computer Science and Engineering in Esslingen. Our offer: The position will be graded up to pay group 13 TV-L (according to the assignment of tasks and personal requirements) The employment rate is up to 100% The position is initially temporary until 14.12.2025 There is the possibility of a PhD Your tasks: Research into various methods of anonymous collection of social and mobility data using methods of cryptographic secure computation (homomorphic encryption, multi-party computation) Adaptation of clustering and machine learning methods for the anonymization of encrypted data Evaluation of the methods (theoretical and empirical) with regard to applicability and resource consumption (runtimes, energy consumption, memory requirements, ...) Programming of the procedures and support in testing the procedures in a field test Scientific processing of the results, presentation at meetings and conferences Your profile: Successfully completed university studies (master's degree/university diploma) in the fields of computer science, mathematics or physics Expertise in the field of cryptography Expertise in machine learning and artificial intelligence desirable Good programming skills e.g. in Python, C++, mobile applications Good communication and presentation skills The application deadline is the 13^th of April 2023. You can submit your application via our application portal. Please include the reference number IT/2303. For further information on the position, please contact: Prof. Dr. Dominik Schoop, dominik.schoop@hs-esslingen.de The Hochschule Esslingen aims to increase the proportion of women in areas in which women are underrepresented and therefore expressly invites qualified women to apply. Severely disabled persons will be given preference if they are suitable. The division of the position is possible if the application situation is appropriate. Esslingen University of Applied Sciences supports its employees with numerous offers such as health promotion, personnel development or the job ticket. In order to reconcile family and career even better, measures are also offered within the framework of the family-friendly university^®. Further information is available at: http://www.hs-esslingen.de Information on the collection of personal data can be found here: https://www.hs-esslingen.de/datenschutz/ contact details Annika Schimpl Kanalstraße 33 73728 Esslingen annika.schimpl@hs-esslingen.de If you apply for this position please say you saw it on Computeroxy Apply

Within the funding guideline for a "Research Network for the Secure Use of Data" the German Ministry of Education and Research (BMBF) is funding the research project "Anonymous Collection and Use of Mobility Data" (AnoMoB). The project aims to develop technical solutions to collect mobility data securely from mobility users with minimal impact on the users’ privacy and to anonymize the sensitive mobility data for further use. Cryptographic secure computation methods will be used for the secure collection of data while the anonymization will employ methods from machine learning. The research project is carried out in cooperation with several companies from the mobility sector and a non-university research institute.

BMBF project profile (in German):
https://www.forschung-it-sicherheit-kommunikationssysteme.de/projekte/anomob

Esslingen University of Applied Sciences is looking for a

research assistant for the project
"Anonymisation of Mobility Data (AnoMoB)"

at the Faculty of Computer Science and Engineering in Esslingen.

Our offer:

The position will be graded up to pay group 13 TV-L (according to the assignment of tasks and personal requirements)
The employment rate is up to 100%
The position is initially temporary until 14.12.2025
There is the possibility of a PhD

Your tasks:

Research into various methods of anonymous collection of social and mobility data using methods of cryptographic secure computation (homomorphic encryption, multi-party computation)
Adaptation of clustering and machine learning methods for the anonymization of encrypted data
Evaluation of the methods (theoretical and empirical) with regard to applicability and resource consumption (runtimes, energy consumption, memory requirements, ...)
Programming of the procedures and support in testing the procedures in a field test
Scientific processing of the results, presentation at meetings and conferences

Your profile:

Successfully completed university studies (master's degree/university diploma) in the fields of computer science, mathematics or physics
Expertise in the field of cryptography
Expertise in machine learning and artificial intelligence desirable
Good programming skills e.g. in Python, C++, mobile applications
Good communication and presentation skills

The application deadline is the 13^th of April 2023.

You can submit your application via our application portal.
Please include the reference number IT/2303.

For further information on the position, please contact:
Prof. Dr. Dominik Schoop, dominik.schoop@hs-esslingen.de

The Hochschule Esslingen aims to increase the proportion of women in areas in which women are underrepresented and therefore expressly invites qualified women to apply. Severely disabled persons will be given preference if they are suitable. The division of the position is possible if the application situation is appropriate. Esslingen University of Applied Sciences supports its employees with numerous offers such as health promotion, personnel development or the job ticket. In order to reconcile family and career even better, measures are also offered within the framework of the family-friendly university^®. Further information is available at: http://www.hs-esslingen.de

Information on the collection of personal data can be found here:
https://www.hs-esslingen.de/datenschutz/

contact details
Annika Schimpl
Kanalstraße 33
73728 Esslingen
annika.schimpl@hs-esslingen.de

If you apply for this position please say you saw it on Computeroxy

Apply