Master Thesis – Human-Machine Interface with Neuromorphic signal processing systems

TN Germany; Aachen; Vor Ort; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

A leading research center in Aachen is offering a master's thesis opportunity focused on developing human-machine interfaces using neuromorphic signal processing systems. Candidates will engage in experimental setups, data analysis, and machine learning applications. This role promotes independent and collaborative work within a diverse team, with flexible arrangements including remote options. Apply promptly as positions are filled as they arise.

Leistungen

Flexible Work Arrangements

State-of-the-Art Equipment

Collaborative Teams

Qualifikationen

• Currently pursuing a master's degree in relevant fields.
• Familiar with machine learning frameworks.

Aufgaben

• Develop measurement setups including electromyographic signal measurement.
• Train neural networks for finger-position estimation.
• Demonstrate real-time finger-position estimation.

Kenntnisse

Machine Learning

Signal Processing

3D Modeling

Ausbildung

Master's Degree in Biomedical Engineering

Master's Degree in Physics

Master's Degree in Computer Science

Master's Degree in Mathematics

Master's Degree in Electrical/Electronic Engineering

Tools

PyTorch

Jobbeschreibung

Master Thesis – Human-Machine Interface with Neuromorphic Signal Processing Systems, Aachen

This position involves developing experimental setups, collecting and analyzing data, and applying machine learning techniques in the context of neuromorphic systems and human-machine interfaces.

Responsibilities:

1. Develop measurement setups including electromyographic signal measurement and motion tracking systems.
2. Collect data to create a dataset for fast finger motion analysis.
3. Train neural networks for finger-position estimation.
4. Demonstrate real-time finger-position estimation using electromyographic signals.
5. Explore in-context learning and neural network architectures to enhance adaptability across subjects and days.

Candidate Profile:

1. Currently pursuing a master's degree in biomedical engineering, physics, computer science, mathematics, electrical/electronic engineering, or related fields.
2. Familiar with machine learning frameworks such as PyTorch.
3. Knowledge of signal processing and experience with EMG or biomedical data is advantageous.
4. Experience with spiking neural networks or neuromorphic computing is a plus.
5. 3D modeling skills are a plus.
6. Ability to work independently and collaboratively.
7. Enthusiasm for experimental work is essential.

Our Offer:

Join a leading interdisciplinary research environment at the Jülich Research Center, with state-of-the-art equipment, collaborative teams, and flexible work arrangements, including remote work options. We value diversity and inclusion and encourage applications from all backgrounds.

Place of employment: Aachen

Application deadline: Until the position is filled. We recommend applying promptly.