Ph.D. Students

The Lab is seeking multiple Ph.D. students (with full Research Assistantship support) on Artificial IntelligenceData Mining, Machine Learning, Big Data Analytics and Artificial Intelligence, starting immediately (i.e., Autumn 2020) until the positions are filled. The students will help develop novel computational techniques for problems in drug development, bioinformatics, medical informatics and health informatics, including, but not limited to, drug property prediction, pharmacovigilance data mining, electronic medical record analysis.

The research is highly data-driven, computation-oriented and primarily focused on methodology development, that is, the development of new and better (not the application of existing) methods/algorithms/models to solve emerging and critical problems in healthcare and medicine domains. The new methodologies that will be developed will also be sufficiently generalizable to be applied to the problems from other domains (e.g., e-Commerce, social networks, system monitoring and diagnosis) that share similar characteristics as the targeted problems in healthcare and medicine domains. The Lab is not, unfortunately, conducting wet-lab biological research, nor focused on mechanism discovery in the biological systems.

Ideal candidates should be self-motivated and determined. They are expected to have a strong background in Math, statistics, Electrical and Computer Engineering, Computer Science and Engineering or Automation. Extensive programming experience in either C/C++, MATLAB or Python is preferred. Basic knowledge and experience in Data Mining and Machine Learning is also preferred.

Ph.D. students will be recruited through the Computer Science and Engineering (CSE) Department (i.e., upon graduation, they will be granted CSE degrees). Thus, they need to apply through CSE and satisfy the CSE admission requirements ( If the students are interested in Spring 2021 or Autumn 2021 admission, please contact Dr. Ning with the updated CV and transcripts.