In this project, the Ph.D. candidate will be partly assigned to two projects:
1) Develop an image processing system that counts white blood cells in the nailfold capillaroscopy
The project will investigate a variety of image processing, computer vision and machine learning techniques to estimate human immune function using nailfold capillaroscopy.
2) Develop a biomedical application using multi-modal physiological signals
In this project, the candidate will analyze multi-modal physiological signals including, but not limited to, Electrokardiogram (EKG), Electromyogram (EMG), photoplethysmography (PPG), Electroencephalogram (EEG) and etc., and will develop a machine learning application using the acquired physiological signals. This project is at an early stage, so the goals and specifications of the application will be specified as the project progresses.
Lab Info: http://bmclhome.wixsite.com/main
- GPA > 3.5 / 4
- TOEFL > 80
- Master's degree in biomedical engineering or computer engineering (or in closely related fields). Students with only bachelor’s degree can also apply, but those students must finish a 2-years master's course first, and will be conditionally accepted as the Ph.D. candidate based on their job performances.
Required skills (optional)
Machine learning, Image processing, MATLAB, Python, Deep learning, Biomedical Engineering
The students will be paid as research assistants and all fees associated with enrollment will be paid by the National Research Foundation of Korea.
Interested candidates are pleased to send their applications to the following email:
Jiwoo You: firstname.lastname@example.org
Prof. Cheolsoo Park: email@example.com