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source

École de technologie supérieure

Postdoctoral Fellow in GNSS Resilience & Secure Navigation for Aerospace École de technologie supérieure in Canada

Degree Level

Postdoc

Field of study

Computer Science

Funding

The position is for 1 year, renewable. No explicit funding or stipend details are provided in the announcement.

Deadline

May 1, 2026

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Country

Canada

University

École de technologie supérieure

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Keywords

Computer Science
Signal Processing
Electrical Engineering
Aerospace Engineering
Inertial Navigation
Flight Testing
Embedded System
Machine learning

About this position

The LASSENA Laboratory at École de technologie supérieure in Montréal, Canada, is seeking a Postdoctoral Fellow to join their advanced navigation security research team. This position focuses on GNSS resilience and secure navigation for aerospace applications, with a strong emphasis on real-world validation and certifiable embedded systems. Research topics include real-time GNSS spoofing detection, jamming scenario modeling, robust GNSS/IMU fusion filters, and experimental validation through lab testbeds and flight campaigns. The ideal candidate will have a recent PhD in Electrical Engineering, Avionics, Telecommunications, or a related field, with expertise in GNSS signal processing, inertial navigation, and/or machine learning for detection. Proficiency in Python, MATLAB, or C/C++ is required, along with hands-on experience in instrumentation or simulation environments such as Skydel or Spirent. Familiarity with aerospace certification standards (DO-178C, DO-229, DO-254) is considered an asset. The position is for one year, renewable, and is part of the ReSMiQ network. Interested candidates should apply via the IEEE Jobs posting (ID 82299376) and submit a CV and cover letter, with optional publications or project summaries. This opportunity is ideal for researchers passionate about advancing navigation security under adversarial and interference conditions in aerospace environments.

Funding details

The position is for 1 year, renewable. No explicit funding or stipend details are provided in the announcement.

What's required

Applicants must have a PhD (obtained within the last 5 years) in Electrical Engineering, Avionics, Telecommunications, or a closely related field. Strong background in GNSS signal processing, inertial navigation, and/or machine learning for detection is required. Proficiency in Python, MATLAB, or C/C++ is essential. Hands-on experience with instrumentation or simulation tools such as Skydel or Spirent is expected. Familiarity with certification standards like DO-178C, DO-229, or DO-254 is a plus.

How to apply

Apply through the IEEE Jobs posting (ID 82299376) at the provided link. Prepare an application package including your CV and cover letter; publications or project summaries are optional. Follow the instructions on the IEEE Jobs site.

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