Our mission is to develop interpretable machine learning algorithms mainly applied to medical data. Your primary focus will be to develop and evaluate interpretable statistical and machine learning algorithms applied to medical data. The main goal is to develop methods for discovering non-linear associations between risk factors and metabolic diseases. The results will aim at helping medical doctors design and implement efficient interventions. You will evaluate your methods by: (a) the performance, computational efficiency, and interpretability of the results; (b) the methods’ robustness to model misspecification; and (c) interacting with experts in the relevant medical field.

The successful applicant should hold, or about to obtain a relevant Ph.D. degree in computer science, statistics, mathematics, or disciplines related to AI or machine learning and should have strong programming skills, and a solid background in statistical theory, machine learning, or artificial intelligence. Preferences will be given to candidates with knowledge in spatial statistics, R-INLA, Template Model Builder, PyTorch, or quantum computing. An initial contract will be given for 2 years, starting at any time from the date of the publication of the job advertisement, with the possibility of subsequent extensions. Fluency in both English and Chinese (Mandarin) is required.

Please send your application in English (current position, CV (max. 2 pages), motivation letter (max. 1 page), transcripts, publications if applicable) as a single PDF to mailbox. Only complete applications will be considered. If you have any questions about the project, our research group, or the position, please do not hesitate to contact Dr. Andre Python at apython@zju.edu.cn.