NeuroEng Lab

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  • MSc Thesis Opportunity: Chronic pain prediction from wearable signals and psychological data

    đź’Š MSc Thesis Opportunity: Chronic pain prediction from wearable signals and psychological data

    đź“Ť Location: Vienna General Hospital, Medical University of Vienna
    ⏳ Duration: 6 months, full-time
    đź“… Start: September/October 2026

    Chronic pain is a complex condition shaped by both physiological and psychological factors. Understanding how these interact could pave the way for more personalized, data-driven approaches to pain assessment and treatment.

    At the NeuroEngineering Lab at the Medical University of Vienna, you’ll join the PainSense project, where we combine wearable sensor data, psychological assessments, and artificial intelligence to better understand and predict pain fluctuations in everyday life. Building on an existing machine-learning pipeline, you’ll explore state-of-the-art AI methods to discover richer patterns in physiological signals and improve pain prediction while keeping the models clinically interpretable.

    What you’ll work on:

    • Investigate how physiological signals relate to changes in chronic pain

    • Develop AI models that learn meaningful representations directly from wearable data

    • Apply explainable AI techniques to understand how the models make predictions

    • Compare your approach with the existing machine-learning pipeline and evaluate its clinical value

    Who we’re looking for:

    • Good programming skills in Python

    • Knowledge of AI and machine learning

    • Experience with deep learning frameworks (e.g., PyTorch), signal processing, or statistical analysis is a plus

    đź“„ Download the complete thesis proposal here.

    đź“© You can apply directly through the website form or by sending your CV, transcript of records, and a short motivation letter to neuroenglab2019@gmail.com.

  • MSc Thesis Opportunity: Use AI to Improve Markerless Motion Capture in Rehabilitation

    đź“· MSc Thesis Opportunity: Use AI to Improve Markerless Motion Capture in Rehabilitation

    đź“ŤLocation: Vienna General Hospital, Medical University of Vienna
    ⏳ Duration: 6 months (full-time)
    đź“… Start: September/October 2026

    Accurately tracking patients during rehabilitation—without physical markers or wearable sensors—could make movement assessment more flexible, and clinically useful.

    At the NeuroEngineering Lab at the Medical University of Vienna, we are developing a markerless motion-capture system that uses multiple synchronized cameras and computer vision to reconstruct human movement. The system is already operational, but one key challenge remains: reliably identifying and tracking the patient in busy clinical environments where therapists, clinicians, or rehabilitation devices may also be present.

    As an MSc student, you will develop and integrate AI-based human segmentation and 3D body-meshing methods to isolate the patient of interest and improve the reliability of movement tracking. Your work will support more accurate and non-intrusive assessment of motor recovery in real-world rehabilitation settings.

    What you’ll work on:

    • Develop and integrate human segmentation and body-meshing methods into the motion-capture pipeline

    • Evaluate and validate the proposed approach through technical testing

    • Explore integration with other rehabilitation technologies and sensing modalities

    Who we’re looking for:

    • Strong programming skills in Python and/or C++

    • Good understanding of computer vision

    • Experience with motion capture is a plus

    Download the complete thesis proposal here. You can apply directly through the website form or by sending your CV, transcript of records, and a short motivation letter to neuroenglab2019@gmail.com.

  •  MSc Thesis Opportunity: Build the Next Generation of Intelligent Neurostimulators

    ⚡MSc Thesis Opportunity: Build the Next Generation of Intelligent Neurostimulators

    đź“ŤLocation: Vienna General Hospital, Medical University of Vienna
    ⏳Duration: 6 months (full-time)
    📅 Start: September/October 2026

    What if electrical stimulation devices could adapt in real time to the body’s own signals?

    At the NeuroEngineering Lab (Medical University of Vienna), we are developing a new generation of intelligent neurostimulation technologies for rehabilitation. Unlike conventional stimulators that deliver fixed stimulation patterns, our novel platform is designed to adapt its output instantly based on biological feedback, opening new possibilities for personalized neurorehabilitation.

    As an MSc student, you’ll work directly on the firmware powering this system, developing deterministic embedded software that guarantees precise timing, safety, and reliable real-time performance. You’ll also explore closed-loop control strategies that use signals such as HD-EMG, pressure sensors, or motion tracking to dynamically adjust stimulation.

    What you’ll work on:

    • Develop low-level firmware in C/C++ for a custom electrical stimulator
    • Design a Hardware-in-the-Loop (HIL) testing framework to evaluate latency and waveform accuracy
    • Implement real-time communication with biological sensors
    • Explore adaptive control and TinyML approaches for intelligent closed-loop stimulation (depending on project progress)

    Who we’re looking for:

    • Strong programming skills (C/C++) for microcontrollers
    • Fundamentals of embedded systems and real-time operating parameters
    • Experience with Hardware-in-the-Loop (HIL) testing or control theory is a plus

    Download the complete thesis proposal here. You can apply directly thorugh the website digital form or sending CV, transcript of records, and a short motivation letter to neuroenglab2019@gmail.com.