PhD Research Engineer

Thales

  • Singapore
  • Permanent
  • Full-time
  • 1 month ago
Location: SINGAPORE, SingaporeThales is a global technology leader trusted by governments, institutions, and enterprises to tackle their most demanding challenges. From quantum applications and artificial intelligence to cybersecurity and 6G innovation, our solutions empower critical decisions rooted in human intelligence. Operating at the forefront of aerospace and space, cybersecurity and digital identity, we’re driven by a mission to build a future we can all trust.In Singapore, Thales has been a trusted partner since 1973, originally focused on aerospace activities in the Asia-Pacific region. With 2,000 employees across three local sites, we deliver cutting-edge solutions across aerospace (including air traffic management), defence and security, and digital identity and cybersecurity sectors. Together, we’re shaping the future by enabling customers to make pivotal decisions that safeguard communities and power progress.Project Title: Physics-based modelling of ionospheric plasma dynamics for accurate positioning and navigationPosition 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 Electrical and Electronics Engineering, or Physical Sciences.
  • Knowledge of electromagnetism and plasma physics is a must
  • Good knowledge of data analytics, AI & machine learning is good to have
  • 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.
At Thales, we’re committed to fostering a workplace where respect, trust, collaboration, and passion drive everything we do. Here, you’ll feel empowered to bring your best self, thrive in a supportive culture, and love the work you do. Join us, and be part of a team reimagining technology to create solutions that truly make a difference – for a safer, greener, and more inclusive world.

Thales