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jobs:causal_inference_postdoc [2020/07/01 16:24] acallaha |
jobs:causal_inference_postdoc [2020/07/01 16:27] acallaha |
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- | ====== Postdoctoral Scholar Position | + | ====== Postdoctoral Scholar Position ===== |
==== Causal inference for risk stratification and clinical decision making ==== | ==== Causal inference for risk stratification and clinical decision making ==== | ||
+ | === Starting September 2020 === | ||
- | About us: We are a group of about twenty doctors, engineers, informatics professionals and students (http:// | + | **About us:** We are a [[http:// |
- | About the project: The research goal of this postdoctoral scholar position is to develop risk stratification tools and treatment effect estimation methods for cardiovascular disease (CVD). The successful candidate will develop personalized treatment effect prediction tools to guide decisions for CVD therapies based on their potential benefit and risk. The position offers the opportunity to work with leading Stanford faculty in Informatics (Nigam Shah), Statistics (Robert Tibshirani), | + | **About the project:** The research goal of this postdoctoral scholar position is to develop risk stratification tools and treatment effect estimation methods for cardiovascular disease (CVD). The successful candidate will develop personalized treatment effect prediction tools to guide decisions for CVD therapies based on their potential benefit and risk. The position offers the opportunity to work with leading Stanford faculty in Informatics (Nigam Shah), Statistics (Robert Tibshirani), |
- | About you: You are a hands-on team member who will collaborate with medical doctors, statisticians and computer scientists to develop methods for causal inference and personalized treatment effect prediction. You will contribute at all levels of the project: designing statistical analysis methods and experiments to evaluate them, implementing robust code, and releasing publicly available software packages. | + | **About you:** You are a hands-on team member who will collaborate with medical doctors, statisticians and computer scientists to develop methods for causal inference and personalized treatment effect prediction. You will contribute at all levels of the project: designing statistical analysis methods and experiments to evaluate them, implementing robust code, and releasing publicly available software packages. |
You will find this project to be a good fit if: | You will find this project to be a good fit if: | ||
- | + | * you are passionate about improving health care using data science | |
- | you are passionate about improving health care using data science | + | |
- | you know causal inference methods inside and out | + | |
- | you are excited to work with rich, sometimes messy, patient-level data | + | |
- | you thrive in dynamic, fast-paced environments | + | |
You look forward to responsibilities that include: | You look forward to responsibilities that include: | ||
- | developing and evaluating novel statistical methods to derive actionable findings from healthcare data of millions of patients | + | * developing and evaluating novel statistical methods to derive actionable findings from healthcare data of millions of patients |
- | programming in R and Python to produce scalable, reusable code | + | |
- | writing manuscripts and progress reports about your research | + | |
- | designing rapid prototypes and making some of them robust | + | |
- | working with a small core team of researchers | + | |
- | involvement in mentoring graduate students and teaching (as appropriate) | + | |
- | You meet all of the following requirements: | + | You meet **all** of the following requirements: |
- | PhD in medical informatics, | + | * PhD in medical informatics, |
- | 2+ years of experience analyzing health data, such as insurance claims and EHRs | + | |
- | fluency in R | + | |
- | excellent written and oral communication in English, with at least one peer-reviewed first-author manuscript | + | |
- | You meet some of the desired qualifications: | + | You meet **some** of the desired qualifications: |
- | experience in processing and analyzing large datasets | + | * experience in processing and analyzing large datasets |
- | knowledge of best practices in data mining and machine learning | + | |
- | app and/or Web development | + | |
- | Interested? Please contact: acallaha@stanford.edu | + | **Interested?** Please contact: acallaha |