About this job

Your Mission:

The goal of the thesis is to develop optimal Bayesian estimators for mapping railway tracks with global navigation satellite system (GNSS) and magnetometer measurements. The magnetometer measures the earth magnetic field that is distorted by railway infrastructure. These distortions are characteristic for a certain position on the track and persistent in time. Multiple runs on the same track therefore allow distinguish different positions based on magnetic field measurements. In combination with GNSS measurements it is possible to create an accurate map containing the geometric track information and the magnetic field.

Responsibilities

In this thesis optimal estimators and smoothers for the track map shall be developed and evaluated. While developing the estimators, different representations of the magnetic field and the track geometry shall be considered. The developed estimators shall be evaluated with simulations and measurement data recorded with different train types.

Profile

• excellent knowledge in mathematics and estimation theory, particularly in Bayesian estimation and SLAM
• solid background in GNSS
• excellent programming skills (preferable in Matlab)
• ability to work independently and to enjoy solving complex problems

Your Benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (m/f/non-binary). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.