Computational Healthcare Analytics Program Research |概述
The Computational Healthcare Analytics Program (CHAP) is an innovative research program in theDepartment of Urologyat Boston Children's Hospital. Our mission is to create and implement revolutionary healthcare analytics by combining cutting-edge medicine and state-of-the-art novel data science. We are an interdisciplinary program, combining physician-scientists and data scientists, that provides the infrastructure and resources to enable the development of next-generation innovations aimed at improving the health and life of children.
Our team is comprised of faculty fromMITandHarvard Medical Schoolwith deep expertise in machine learning algorithms and artificial intelligence. These advanced analytics provide unprecedented tools with which we can identify highly complex patterns from vast amounts of data, allowing robust predictions. These insights will revolutionize healthcare by assisting clinicians in making the most individualized, safe, and cost-effective decisions for their patients.
Join the CHAP team!
Post-doctoral fellows and research scientists
The Computational Healthcare Analytics Program (CHAP) at Boston Children’s Hospital is seeking a post-doctoral research fellow or research scientists. The fellow/researcher will join a multidisciplinary team of clinicians, mathematicians, informaticists, engineers, statisticians, and operations researchers to develop cutting-edge healthcare analytics with real-world implementation.
该职位针对具有机器学习算法开发和应用方面具有专业知识的高度积极进取和熟练的个人，并对医疗保健产生了浓厚的兴趣。
Primary duties and responsibilities
- develop novel predictive/prescriptive models and algorithms in healthcare
- statistical analysis of large clinical datasets from national and regional sources
- 独立于多个正在进行的项目，具有灵活性来适应新的优先级
- present the work in form of scientific publications and oral communications to the scientific community
The group is located at the Boston Children’s Hospital, a teaching hospital affiliated with Harvard University.
Qualifications
- strong proficiency with R and Python; proficiency with other major programming languages for data science and statistical analysis (e.g. Julia, SAS, Matlab) is a plus, as well as other programming languages (e.g. Julia, SAS, Matlab)
- 熟悉机器学习和统计中的现代分析范例
- familiarity with a wide range of popular supervised and unsupervised machine learning models
- strong communication skills and ability to effectively translate scientific concepts to multidisciplinary personnel
- demonstrated ability and experience in advanced analytics
- highly proficient in spoken and written English and scientific writing skills.
The candidates for post-docs or research scientists must hold a PhD or equivalent degree by the start of employment.
How to apply
Interested applicants should send a cover letter outlining research experience and interests, curriculum vitae (CV), GitHub account name (if available), and the names and contacts of three referees to Dr. Hsin-Hsiao Scott Wang, MD, MPH, MBAn (scott.wang@childrens.harvard.edu).