Role & responsibilities
- Process and analyse physiological signals such as PPG, ECG, EEG, GSR/EDA and motion sensor data.
- Perform signal preprocessing, filtering, noise reduction and artefact removal.
- Conduct time-series analysis and feature extraction of dynamic biosignals.
- Develop signal-processing algorithms for health monitoring applications.
- Build and implement Python-based algorithms and machine-learning models.
- Develop health-monitoring metrics and algorithms for HRV, stress, sleep and cognitive performance.
- Work with experimental hardware, wearable sensors and prototypes for data collection and signal acquisition.
- Contribute to the deployment and validation of wearable health-monitoring systems, including regulatory trials. Preferred candidate profile
- 3+ years of experience working on physiological signal processing and wearable health-monitoring systems.
- Strong expertise in DSP,



biosignal analysis and algorithm development.
- Hands-on experience with PPG, ECG, EEG, GSR/EDA and motion sensor data.
- Proficiency in Python and relevant libraries such as NumPy, SciPy, pandas, scikit-learn, TensorFlow or PyTorch.
- Experience in time-series analysis, feature extraction and machine-learning models.
- Practical exposure to experimental research, data collection, signal acquisition and wearable sensor prototypes.
- Experience with real-world deployment or regulatory trials in health-monitoring applications.
- Master's or PhD in Biomedical Engineering, Electrical/Electronics Engineering, Neuroengineering or a related discipline.
- Strong communication skills, curiosity and ability to work in a rapid-growing, cross-functional environment.

📌 Bioelectronics Engineer (New Delhi)
🏢 Neha Chauhan Narang
📍 New Delhi