【简介】博士后招聘网整理分享“美国加州大学洛杉矶分校机器学习&数据分析和分享平台博士后职位”，浏览查询更多博士后招聘计划请访问博士后招聘网。

Postdoctoral Researchers: Machine Learning & Data Analytics and Sharing Platforms : Los Angeles, CA, United States

Two NIH-supported postdoctoral positions are available in the NIH Big Data to Knowledge (BD2K) Centers of Excellence. The NIH BD2K Initiative is a global scientific initiative supported by the NIH Office of the Director.

The first position is co-mentored by Dr. Peipei Ping, director of the NIHHeartBD2K Center of Excellence at UCLA, and Dr. Jiawei Han, director of the NIH BD2K KnowEng Center of Excellence at the University of Illinois, Urbana-Champaign. The position will be located at UCLA, with strong collaboration and interaction with both BD2K Centers.

The second position is co-mentored by Dr. Peipei Ping, director of the NIH HeartBD2K Centers of Excellence at UCLA, and Dr. Wei Wang, Director of the Scalable Analytics Institute at the Henry Samueli School of Engineering at UCLA.

Successful applicants will have an exciting opportunity to work with a group of highly talented and creative investigators on projects focusing on one of the following of these two areas of Data Science: 1) machine learning, specifically text mining both biomedical literature and electronic health records; and 2) the development of analytics and data sharing platforms. Salaries are commensurate with experience based on the NIH scale.

Qualifications:

Candidates should have or be very close to obtaining a PhD.

Applicants must have a strong background in quantitative biology, or a related field.

Experience in computation is highly desirable, but not required.

It is essential that applicants have previously demonstrated a passionate work ethic, strong enthusiasm for Big Data research, and a propensity for scientific achievement.

All Applications should include the following:

Curriculum vitae;

Contact information of at least three references;

Brief description of past research experience and accomplishments, current and future research interests, and expected availability date.

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