Postdoctoral Fellow

This project is about cancer research related to cancer genomics, and the application of machine learning to develop diagnostic tools for the clinical setting. The research is part of an ongoing paradigm shift in cancer diagnosis (classification) that received much attention recently. The automated recommender-based software tool can guide clinicians with disease diagnosis (classification). The candidates with prior knowledge of brain cancer (glioma) will be encouraged to apply as we will use it as proof of principle as initial work.

This work requires knowledge and experience in cancer research, next generation sequencing, and biomedical data analysis, while clinical research experiences will be considered as an asset.

The ideal candidate should have strong knowledge of Cancer Research and Molecular Diagnostics. Clinical research experience in hospital or industrial settings will be considered as an additional merit. This position is also a part of collaboration with leading hospitals in Toronto. A short-list applicant ONLY will be contacted for a formal interview.

Duties:

• Collect various clinical and pathological information and establish biomarkers to build smart risk recommender.
• Analyze clinical data and associated biological data with patient outcomes (treatment and survival).
• Test machine learning models to the desired level of prediction accuracy.
• Work with clinicians to analyze the explainable patient-specific decisions.
• Publish significant results in national/international conferences and journal papers.
• Communicate progress with supervisor and team members during periodic meetings.

QUALIFICATIONS

QUALIFICATIONS:

PhD