Job Details
- Expires 24 November 0 days left to apply
- Reference number: GIB001
- Province: Western Cape
- Type of engagement: Fixed term contract
- Posted: October 24th
- Remuneration package: Please note that postdoctoral fellows are not appointed as employees and are therefore not eligible for employee benefits. Postdoctoral fellowships are also awarded tax free.
Background to Position
Alstom and Ubumbano Rail, through an agreement with PRASA, have formed an exciting consortium called Gibela – with a 70:30 equity split respectively.
The consortium is charged with the delivery of 600 modern commuter trains over the next 10 years, and if that’s not enough, it is also charged with providing optimal maintenance support, for the next 19 years.
The Chair at Stellenbosch University is funding research in trackside monitoring applications and asset management technologies for Gibela passenger trains by leveraging the potential of digital twin technology.
Job Description
The foremost aim of the advertised post-doctoral position is to establish research into digital services that inform on the condition of Gibela trains in operation. This may entail that rail sections or trainsets are equipped with additional software tools, services, capabilities, and data access which will provide information to manufacturers, maintainers and asset operators to inform decisions about train maintenance. The emphasis of this work will require a balance between applied research that is relevant to industry and research that has academic merit.
As a postdoctoral fellow, you will assist the academics of the Gibela Engineering Research Chair with specific research, technical analysis and student supervision under the academic directive of the host. As a postdoctoral fellow, you will be expected to write at least two full-length, peer-reviewed journal articles per year. With a proviso of delivering a paper, funding is available to attend at least one international conference each year. The work will entail travel between Stellenbosch University and the Gibela manufacturing plant situated in Dunnottar, Ekurhuleni, Gauteng (approximately 50kms east of Johannesburg), as well as to five geographically dispersed depots, where you will perform and oversee monitoring activities.
Key Performance Areas:
Track-side sensor assembly:
A trackside sensor assembly will be assembled to monitor the condition of Gibela trains. It is envisioned that this trackside sensor assembly should be established on the 1.2 km test track section at the Gibela Manufacturing Plant where low speed commissioning tests on newly built trains are carried out. Such sensor systems can be extended to trackside monitors at the Gibela train depots. In this way newly manufactured trainsets can be characterised upon manufacturing and monitored during operation. As such a significant requirement of the advertised position is a competency in mechanical measurements (strain, vibration, optical, thermal).
Signal processing techniques are crucial to extract rich features from monitoring data:
The latest literature indicates the use of techniques such as wavelet analysis, empirical mode decomposition and Hilbert transforms in track monitoring applications. The ideal candidate will demonstrate experience and a keen interest in signal processing techniques to elicit features from digital signals that may be used for anomaly detection and fault diagnosis.
Data project for Gibela monitoring data:
Monitoring data will be ingested into a database with the associated meta-data. All data will be consolidated and referenced on a purposely maintained server. A background in data engineering or understanding of databases is an advantage. The work will entail collaboration with software and data engineering specialists to select and develop a data model.
Student supervision and leadership:
The Gibela brand persona is people centric, optimistic and future focused whilst striving for precision and excellence. The ideal candidate would complement this identity by reflecting enthusiasm for Gibela work, the supervision of students and the creation of a positive and productive work environment.
- 2 Year appointment
Inherent Criteria
Having graduated with a PhD in Engineering from a recognised academic university within the last five years, your thesis/dissertation involved rail or rolling stock / monitoring technology / measurements / signal processing or an applicable field relevant to this position. Ideally, you are a South African citizen, although this is not essential. Your experience in conducting engineering research at an advanced level and publishing in reputable journals and conferences is highly evident, as is your experience with measurement campaigns, instrumentation and signal processing in the field and/or laboratory. Such experience includes the use of vibration and acoustic measurement equipment. You are known for your excellent command of spoken and written English language. You have at least two journal articles accepted for publication in a peer-reviewed journal and you have supervised and guided students.
From a discipline perspective, you should be seasoned in the following:
- Mechanical Engineering
- Acoustics
- Computer Vision
- Electrical Engineering.
