Master Thesis (d/m/w) for neuromorphic on-board processing for Telecom Satellites

Key Responsibilities

• Use neuromorphic processing evaluation hardware
• Translate "classic" ANNs to SNNs
• Develop and train SNNs for Earth Observation data and time-series data
• Compare key metrics to other state-of-the-art space-grade ML hardware platforms
• Research about on-board continuous, online learning
• Demonstrate space-targeted AI algorithms on real evaluation hardware

Requirements

Education

Enrolled full-time student in Artificial Intelligence, Telecommunication Engineering, Electrical Engineering, or similar field

Required Skills

• Embedded programming (Python, C, C++)
• Deep Neural Network modelling with common frameworks (Tensorflow, PyTorch)
• Fluent English
• German (asset)

Benefits

• Attractive salary
• Work-life balance with 35-hour week (flexitime)
• International environment
• Opportunity to network globally
• Work with modern/diversified technologies
• Close contact with interfaces
• Participation in weekly team meetings
• Opportunity to participate in Generation Airbus Community