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Student Research Assistant (m/w/d) Autonomous E-Shuttle service with inductive charging

14.09.2021, Studentische Hilfskräfte, Praktikantenstellen, Studienarbeiten

---> http://go.tum.de/967036 <--- We are looking for a student research assistant (10 hours per week, possibly remote) to contribute to a research project dealing with planning the operation of a autonomous E-Shuttle service with inductive (static & dynamic) charging. A fleet of 2 autonomous E-Shuttles will be deployed in Bad Staffelstein. These will be charged inductively on stationary charging pads and coils embedded in the road's surface, such that the shuttles can be charged autonomously during service. Your task will be to aid in the development and implementation of the nessesary algorithms to plan the operation of this shuttle service.

Further Information

The project:

  • Deployment of 2 autonomous shuttle-busses in the area of Bad Staffelstein
  • Charged inductively on charging pads (stationary) and via road-embedded coils (while driving)
  • Partners:
  • Valeo
  • IGSolar
  • Magment
  • Bergische Universität Wuppertal
  • Bad Staffelstein

Your role/Our offer:

  • Contribute to a real-world case-study in the context of autonomous electro-mobility with inductive charging
  • Work on a bleeding edge Python/C++-20 implementation of a state-of-the-art Branch-and-Price algorithm
  • Develop tooling to support data scraping, analysis & visualization
  • Participate actively in research

Your profile:

  • Bachelor’s Degree in Computer Science, (Electrical) Engineering, Mathematics or a similar program
  • (Basic) proficiency in a modern systems programming language (C++, Rust, ...)
  • (Basic) proficiency in another general purpose programming language (Python, Go, ...)
  • Ability/Desire to work in a linux driven environment
  • Previous experience in optimization (OR), with autonomous vehicles and/or (inductive) charging is a plus!
  • Experience with (full-stack) web development (Vue.js, Flask/FastAPI/Express.js) is a plus!

About us: The professorship of operations and supply chain management focuses on the development of algorithms in the fields of operations research and machine learning applied to transportation systems, logistics networks, and supply chains. Visit https://osm.wi.tum.de for more information.

Application: Are you interested and would like to chat about the project? Send your CV and other documents or references (e.g., github/leetcode/etc. account) to patrick.sean.klein@tum.de.

Kontakt: patrick.sean.klein@tum.de

More Information

http://go.tum.de/967036

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