- Design, characterize and test algorithms to analyse physiological data (ECG and PPG)
- Collect, analyse and draw insights from real world healthcare data from biosensors
- Mine existing biomedical signal and healthcare datasets to guide algorithm design and optimization
- Characterize performance of cardiac algorithms on annotated proprietary biosignal data sets as per EC57 guidelines
- Perform comprehensive evaluation of new concepts using bench, preclinical, and clinical data collection and analysis
- Master or PhD in Electronic Engineering, Computer Science, Biomedical Engineering or related program with good signal processing skills
- Hands on experience with development of signal processing projects, including noise detection, pre-processing, feature engineering, machine learning model building and performance evaluation.
- Experience working with ECG, PPG, and other types of biomedical/healthcare data is a bonus
- Background in or exposure to healthcare data, human physiology or cardiology is good
- Proficient with spectrum analysis, pattern recognition, supervised learning, hypothesis testing.
- Proficient with programming in Python. Good programming in R or C/C++ is a plus.
- Good research ability and critical thinking skills.
- Excellent written and verbal communication skills
Interested candidate, please submit your updated resume in MS WORD format to: firstname.lastname@example.org
We regret that only shortlisted candidates will be notified.
Name: Yong Whei Jie
Registration Number: R1110096
EA Licence Number: 02C3423
Octavius, Whei Jie Yong EA License No.: 02C3423 Personnel Registration No.: R1110096