【简介】博士后招聘网整理分享“美国德克萨斯大学MD安德森癌症中心2021年招聘博士后职位（生物信息学、计算生物学方向）”，浏览查询更多博士后招聘计划请访问博士后招聘网。

美国德克萨斯大学MD安德森癌症中心2021年招聘博士后职位（生物信息学、计算生物学方向）

Postdoctoral fellow

The University of Texas MD Anderson Cancer Center

A full-time postdoctoral fellow position is available in Dr. Wenyi Wang’s lab, at the Department of Bioinformatics and Computational Biology at the University of Texas MD Anderson Cancer Center. Dr. Wang’s laboratory builds an extensive research program on tumor heterogeneity and evolution, and cancer risk prediction modeling. Development of statistical methods and tools under this program aims to address clinically relevant questions in cancer biology and genetics, such as developing novel biomarkers for the risk stratification, treatment selection, and prognostication of cancer. For further information, visit the lab website at

https://odin.mdacc.tmc.edu/~wwang7/.

The proposed start date is June 1, 2021. The postdoctoral fellow will be mentored directly by Dr. Wang, with possible co-mentorship from qualified MD Anderson faculty members, or other institutions in the Texas Medical Center, including Rice University. Applications will be accepted until the position is filled.

Position Qualifications

A Ph.D. degree in statistics, biostatistics, applied mathematics, bioinformatics, computer science or a related field. Extensive experience with R and Python, prior experience in computational biology are required. Candidates should also have a background in any of the following areas: cancer biology, graphical models, semi-parametric Bayesian models, or penalized likelihood methods.

To apply, send a curriculum vitae, a research statement and three references titled “Postdoctoral application – Name” to wwang7@mdanderson.org.

Salary – competitive.

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

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