Accurately predicting disease outcomes can have a significant impact on patient care, leading to early detection, personalized treatment plans, and improved clinical outcomes. Machine learning algorithms provide a powerful tool to achieve this goal by identifying novel biomarkers and drug targets for various diseases. By integrating machine learning algorithms with biological data, you will have the opportunity to push the boundaries of precision medicine and contribute to algorithms that can revolutionize the field.
School
Research Area
Machine learning | Bioinformatics | Single-cell analysis
- Research Environment
- Expected Outcomes
- Reference Material/Links
- Our team
Your main contact is Dr Raymond Louie, who has over 10 years experience in developing algorithms to solve biological problems. There will also be opportunity to work with researchers in the Faculty of Medicine and Health at UNSW.
We are looking for a highly motivated student who is passionate about applying computational skills to solve important health problems. Don’t worry, no specific biological knowledge is necessary, the important thing is you are enthusiastic and willing to learn. Please get in touch if you have any questions.
You will have the unique chance to work on state-of-the-art machine learning algorithms, and apply these algorithms to biological data for different diseases, such as cancer. The specific outcomes include a literature review of the machine learning algorithms applicable to single-cell biological data, and the application or development of these algorithms to single-cell data.
