Bioelectronics Engineer

Role & responsibilities

• Signal Processing Expertise: In-depth experience in signal preprocessing (filtering, noise reduction, artifact removal) for physiological signals such as PPG, ECG, EEG, GSR/EDA, and motion sensors.
• Time Series Analysis: Proficiency in handling time-series data, feature extraction, and analysis of dynamic biosignals.
• Python Expertise: Strong proficiency in Python for data processing, algorithm development, and machine learning model implementation (libraries like NumPy, SciPy, pandas, scikit-learn, TensorFlow, PyTorch)
• Health Monitoring and DSP: Experience in Digital Signal Processing (DSP) and health parameter monitoring algorithms, specifically in applications related to biosignal analysis (heart rate variability, stress, sleep, cognitive performance).
• Project Deployment & Machine Learning: At least 3 years of experience contributing to health monitoring systems, including real-world deployment or regulatory trials, with a strong understanding of machine learning models and mathematical modeling for biosignal analysis.

Preferred candidate profile

• You have previous direct experience with experimental research, including data collection, signal acquisition, and working with experimental hardware (sensors, wearable prototypes, etc.).
• You have strong expertise in signal processing, algorithm development, and health parameter monitoring for IoT-based wearable devices
• Masters/PhD in Biomedical Engineering, Electrical/Electronics Engineering, Neuroengineering, or a related field.