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【访学招聘】美国斯坦福大学正在招收访问学者、博士后!

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斯坦福大学(Stanford University),简称斯坦福,位于美国加州旧金山湾区南部帕罗奥多市境内,于1885年成立、1891年开始正式招生,占地约33平方公里(8180英亩),是美国占地面积第六大的大学。与旧金山北湾的加州大学伯克利分校共同构成了美国西部的学术中心,并负责运行管理SLAC国家加速器实验室、胡佛研究所等机构。

要出国访问学习的小伙伴看过来啦,斯坦福大学计算机科学,医学信息学,生物信息学或相关的定量学科方向正在招收访问学者、博士后!51访学网小编每周定时更新最新的访学招聘信息,感谢关注51访学。

We are a group of about twenty doctors, engineers, informatics professionals and students focused on enabling better care using existing health data. 

We develop novel methods to learn from patient-level health data including structured health encounter records, clinical notes, insurance claims, diagnostic imaging, and clinical trial data. 

A major research thrust is to answer clinical questions that enable better medical decisions using electronic health records (EHRs) and insurance claims data, via a consultation service that uses aggregate patient data at the point of care. 

We also have an active research program to research safe, ethical, and cost-effective strategies for predictive models to guide mitigating care actions.

Our research group is part of the Department of Medicine at Stanford. 

The primary research focus of this postdoctoral or visiting scholar position is flexible, and will involve developing and advancing methods for data-driven bedside decision making, or machine learning for health system-level improvements. 

An additional operational focus will involve being responsible for our group’s data analysis and compute infrastructure, including managing dataset ingestion and cleaning, database management, and supporting the cloud compute needs of our lab members. 

The position offers the opportunity to work with leading Stanford faculty in Informatics, Statistics, and Medicine as well as an opportunity to build real-world credibility in DataOps.

Detail Requirements:

You are a hands-on team member with research experience who collaborates with medical doctors, statisticians and computer scientists to advance methods for clinical decision making using observational health data and/or improving patient care via machine learning. 

You will manage our data and compute infrastructure to turbo-charge the research of our entire team. 

You are a contributor at all levels: designing methods as well as experiments to evaluate them, implementing robust code, and coordinating with our collaborators.

  • in CS, medical informatics, bioinformatics or related quantitative discipline

  • experience in processing and analyzing large datasets

  • 3+ years database management experience

  • 3+ years of coding experience

  • fluency in linux system administration

  • excellent written and oral communication in English, with at least one peer-reviewed first-author manuscript

You meet some of the desired qualifications:

  • 1+ years of experience analyzing health data, such as insurance claims and EHRs

  • knowledge of best practices in data mining and machine learning

  • app and/or Web development

  • GCP system administration

Contact information

Interested? Please contact: acallaha@stanford.edu

Required Application Materials: Cover letter, CV, 2+ references

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