Engineer / Researcher — IMU Sensing & Behavioral Biometrics

About the Role

Rebellion Systems is building AuthenSee, a privacy-preserving authentication protocol powered by zero-knowledge proofs. One of our most exciting research directions: using IMU sensor data (accelerometer, gyroscope) as a behavioral biometric factor — proving you're you by the way you move.

We're looking for an Engineer/Researcher to lead R&D on IMU-based behavioral biometrics for authentication. You'll explore how motion signals from smartphones can be captured, featurized, and verified inside ZK circuits — turning the way someone picks up their phone into a cryptographic identity factor.

This role is also open as a Master's thesis opportunity or research internship. If you're a graduate student working on signal processing, behavioral biometrics, or applied cryptography, we'd love to fund your thesis or host an internship around this problem. We can shape the scope together.

What You'll Do

• Research and prototype IMU-based behavioral biometric authentication
• Design feature extraction pipelines for 3-axis accelerometer and gyroscope data
• Investigate signal processing techniques for motion pattern recognition (gait, device handling, interaction dynamics)
• Explore how extracted features can be quantized and hashed for use inside ZK proof circuits
• Evaluate false acceptance / false rejection rates across diverse user populations and device types
• Prototype on-device inference pipelines for real-time feature extraction on iOS and Android
• Collaborate with the ZK engineering team to assess feasibility of proving behavioral biometric claims in zero-knowledge
• Survey academic literature on behavioral biometrics, continuous authentication, and ML-in-ZK approaches (e.g., Rarimo's model)
• Publish findings and contribute to open research where appropriate

Requirements

• Background in signal processing, sensor systems, machine learning, or applied mathematics
• Familiarity with IMU sensors (accelerometers, gyroscopes) and their data characteristics
• Experience with feature extraction from time-series data
• Proficiency in Python, and/or Rust or C++ for performance-critical work
• Ability to read and critically evaluate academic papers
• Strong experimental methodology — you design rigorous experiments and care about statistical validity
• Self-directed and comfortable with open-ended research problems

Nice to Have

• Experience with mobile sensor APIs (Core Motion on iOS, SensorManager on Android)
• Background in behavioral biometrics, gait recognition, or continuous authentication
• Familiarity with zero-knowledge proof systems (SNARKs, STARKs) or interest in learning
• Experience with ML model deployment on mobile / edge devices
• Knowledge of privacy-preserving machine learning techniques
• Publications in relevant venues (IEEE S&P, USENIX Security, CHI, MobiSys, SenSys, etc.)

What We Offer

• Competitive compensation (salary, stipend, or thesis funding — depending on arrangement)
• Flexible structure: full-time role, research internship, or funded Master's thesis — we'll shape it together
• 100% remote — work from anywhere in Europe
• Async-first culture with minimal meetings
• Direct collaboration with the founding team
• Conference and research budget
• Work on a genuinely novel problem at the intersection of sensor systems, cryptography, and privacy
• Your research has a clear path to production in a real product used by real people