AIRO Young Opportunity
Expires
15 Nov 2018
Institution
University of Applied Sciences Karlsruhe - Technology and Economics
Country
Germany
Description
At the earliest possible date, the following PhD position (50% part-time) is to be filled at the Institute for Transport and Infrastructure.
Responsibilities:
Participation in the BMBF research project "Reliability in Smart and Big Data for Public Transport". Analysis of sensor data for entry, exit, and transfer processes in public transport. Development and implementation of an optimization approach to accelerate the transfer processes in nodes of public transport networks.
Requirements:
- Completed university education in computer science, business informatics, traffic science, physics, mathematics, economics / engineering and related degree programs
- Interest in working with data and software
- Good knowledge of quantitative analysis methods is desirable
- Scientific interest, high motivation for research
Employment is initially limited to 31 October 2019. Thereafter, the contract may be extended until 30 June 2021. Depending on on personal experience, the classification is made according to the remuneration group 10 TV-L.
More info at the link
Responsibilities:
Participation in the BMBF research project "Reliability in Smart and Big Data for Public Transport". Analysis of sensor data for entry, exit, and transfer processes in public transport. Development and implementation of an optimization approach to accelerate the transfer processes in nodes of public transport networks.
Requirements:
- Completed university education in computer science, business informatics, traffic science, physics, mathematics, economics / engineering and related degree programs
- Interest in working with data and software
- Good knowledge of quantitative analysis methods is desirable
- Scientific interest, high motivation for research
Employment is initially limited to 31 October 2019. Thereafter, the contract may be extended until 30 June 2021. Depending on on personal experience, the classification is made according to the remuneration group 10 TV-L.
More info at the link