Position as PhD Student in Big Data Engineering and Federated Machine LearningFull PhD

  • English

    Working Language

  • Hamburg

    Location

  • 04 Dec 2024

    Application Deadline

  • 01 Jan 2025

    Starting Date

Overview

Open Positions

1

Time Span

01 Jan 2025 for 3 years

Application Deadline

04 Dec 2024

Financing

yes

Type of Position

Full PhD

Working Language

English

Required Degree
  • Diplom
  • Diplom (university of applied sciences)
  • Master
Areas of study

Applied Computer Science, Computer Science, Engineering Informatics, Media Informatics, Medical Informatics, Practical Computer Science, Software Engineering, Information Systems and Management

Description

Description

The Institute for Data Engineering at Hamburg University of Technology (TUHH) https://www.tuhh.de/ide/homepage.html for the earliest possible date, is looking for a:

Research Associate / PhD student (m/f/d)

full-time and preliminary limited until December 2027. The position is funded by the German Center for the Mobility of the Future as part of the Next Generation City Networking (NGCN) project. The remuneration is in accordance with TV-L 13.

The NGCN project will investigate solutions for the mobility of the future whose systemic approach combines an innovative radio and communication infrastructure with a data-based model platform for the 15-minute city and the emergency aid use case. The use of wireless innovations and the use of new data lakes in NGCN connect urban IoT systems and AI applications in the sense of a groundbreaking AIoT for cities.

The Institute for Data Engineering at TU Hamburg conducts research and teaching at the intersection of data engineering and distributed systems, with a particular focus on Distributed Stream Processing, Federated Learning / Artificial Intelligence at the Edge, Blockchain Technologies, and the Internet of Things.

Your Tasks

  • Conducting independent and high-quality research in the field of data engineering and federated learning for the mobility scenarios of the future, aiming at the integration of Internet of Things (IoT) data and the usage of federated machine learning techniques for exploiting the data. 
  • Publishing your research results in peer-reviewed journals and presenting at international conferences.
  • Collaborating with our industrial partners, with other researchers, and visiting other (national and international) research institutes for academic exchanges.

Your Profile

  • Diploma or Master university degree in computer science, informatics, business informatics, or a related discipline is expected
  • Very good programming skills
  • Very good scientific communication and writing skills
  • Experience in Big Data technologies, IoT technologies, and/or federated machine learning is very welcome
  • In-depth interest in scientific problems and the motivation for independent and goal-oriented research
  • The willingness to contribute to an industry-oriented scientific project aiming at fundamental research results

Our Offer

  • We offer you the opportunity for continuing personal and professional education
  • The chance to conduct research (theoretical and experimental) within a young and international team, which is delivering very important contributions to data engineering and federated learning research
  • The opportunity for stays abroad at international partner universities
  • To become part of a creative team at an aspiring university and in one of the most livable cities in the world

For further information please contact Prof. Stefan Schulte (stefan.schulte@tuhh.de) and see www.tuhh.de/ide.

We particularly encourage women to apply. Due to their underrepresentation, they will be given priority in cases of equal suitability, qualifications, and professional performance.

Please send your complete application documents (cover letter, curriculum vitae in table form, proof of completed training and/or university degree, job references or certificates of employment, and latest thesis) via the online application system at https://stellenportal.tuhh.de/sdzmz

We look forward to receiving your online application by December 4th, 2024.

Required Documents

Required Documents
  • Motivation letter
  • CV
  • Certificates
  • Transcripts
  • References

Application

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