Research Scientist (1-year contract), SCIS

Job Description

• This position is forSchool of Computing and Information Systems (SCIS).
• Design and develop wearable hardware prototypes, including novel form factors, for reliable PPG sensing and on-device heart rate estimation under real-world conditions.
• Develop signal processing and machine learning algorithms for robust physiological parameter estimation usingPPG and auxiliary sensing modalities.
• Design and implement resource-efficient software pipelines for edge/on-device physiological monitoring underhardware and energy constraints.
• Conduct large-scale user studies and data collection across participants with varying demographics, physiological conditions, and activity levels.
• Publish in top-tier academic venues (SCIS A./A venues).
• Other duties as assigned.

Qualifications

• Minimum PhD degree in Computer Science, Biomedical Engineering, Information Systems or closely related disciplines.
• Minimum 2 years of relevant research experience in wearable-based sensing, PPG signal analysis, embedded device, or signal processing.
• Excellent academic record with publications in CS ranking A. venues (SenSys, PerCom, MobiSys, MobiCom,IMWUT).
• Experience with the deployment and use of Deep Learning frameworks (e.g., TensorFlow or Pytorch), includingthe design of neural networks-based models for activity recognition.
• Proficiency in programming software/languages such as Python and C is required.
• Experience with sensing using wearable devices, especially earables, is required.
• Practical experience with resource-efficient algorithms for human activity recognition and domain adaptation is highly desired.
• Demonstrated experience and know-how of signal processing is a strong plus.
• Good analytical, technical and problem-solving skills.
• Research background in Human-Computer Interaction is preferred.
• Self-motivated individual who can work independently and collaboratively with team members.

• This position is forSchool of Computing and Information Systems (SCIS).
• Design and develop wearable hardware prototypes, including novel form factors, for reliable PPG sensing and on-device heart rate estimation under real-world conditions.
• Develop signal processing and machine learning algorithms for robust physiological parameter estimation usingPPG and auxiliary sensing modalities.
• Design and implement resource-efficient software pipelines for edge/on-device physiological monitoring underhardware and energy constraints.
• Conduct large-scale user studies and data collection across participants with varying demographics, physiological conditions, and activity levels.
• Publish in top-tier academic venues (SCIS A./A venues).
• Other duties as assigned.