Location: SINGAPORE, Singapore
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Thales established its presence in Singapore in 1973 to support the expansion of aerospace-related activities in the Asia-Pacific region. Throughout the last four decades, the company grew from strength to strength and is today involved in the primary businesses of Aerospace (including Air Traffic Management), Defence & Security, Ground Transportation and Digital Identity & Security. Thales today employs over 2,100 people in Singapore across all its business areas.
Project Title: Physics-based modelling of ionospheric
plasma dynamics for accurate positioning
and navigation
Position Summary:
- Modern transportation systems depend heavily on accurate GNSS-based positioning, which is greatly affected by the ionospheric state such as electron density and plasma bubble irregularity. Depending on the ionopsheric plasma dynamics, the GNSS signals transmitted by navigation satellites might be attenuated and/or distorted when received by GNSS receivers onboard aircrafts and ships.
- The Research Engineer will work on PhD project, which aims to study and analyse the physics of ionospheric dynamics, scintillation and plasma bubble irregularities for accurate positioning and navigation.
Responsibilities:
- To perform research on physical causal modelling and efficient simulations of GNSS signals through the ionospheric multilayers, for better understanding of various electromagnetic phenomena including signal propagation and refractions. The PhD student is expected to apply both classical physics modelling techniques and state-of-the-art machine learning techniques to develop an ionospheric anomaly threat model to predict important ionospheric parameters for GNSS positioning and navigation.
Requirements:
- Bachelor's or Master's degree in Engineering, or Physical Sciences.
- Good knowledge of data analytics, AI & machine learning and plasma physics.
- Keen interest to contribute to improving the safety of aviation and maritime systems.
- Good communication and presentation skills, with appetite for engagement with the industrial supervisor and collaborators.
- Self-starter with good analytical and problem-solving skills.
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