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Brown University – Postdoctoral Research Associate in Biostatistics and Data Science
Company NameBrown University
Position TitlePostdoctoral Research Associate in Biostatistics and Data Science
Company Information
Department of Biostatistics & Brown Data Science Institute
Duties and Responsibilities
* Conduct original methodological research in statistics, machine learning, epidemiology, and/or biomedical data science
* Develop and evaluate new methods for causal and predictive inference, and decision-making using large-scale and/or multi-source data
* Collaborate with faculty and research partners on applied and methodological projects
* Lead and contribute to peer-reviewed publications
* Present research findings to academic and interdisciplinary audiences
* Participate in the intellectual life of the Department of Biostatistics and the Brown Data Science Institute
Position Qualifications
PhD or equivalent doctoral degree in biostatistics, statistics, computer science, data science, epidemiology or a related quantitative field by the start date.
The successful candidate will demonstrate:
* Strong methodological training in (bio)statistics and/or machine learning
* Interest in developing rigorous methods for biomedical, clinical, or public health data
* Experience with statistical computing (R and/or Python) and reproducible research workflows
* A strong publication record relative to career stage
* Excellent scientific writing and communication skills
* Ability to work effectively in interdisciplinary research settings
Experience with one or more of the following is preferred:
* Randomzied trials, electronic health records, claims data, registries, or other real-world health data
* Causal inference, conformal inference, federated learning, transfer learning, or fairness-aware machine learning methods
* Collaborative work with applied investigators in health-related domains
Salary Range70,000-80,000
Benefits
Postdoctoral Research Associates are employees of Brown University, who are eligible for a full range of benefits.
Application Instructions
Applicants
should submit a cover letter describing research experience, career goals, and interest in the
position, CV, one representative publication, and contact information for three references via
Interfolio: https://apply.interfolio.com/183934. Candidates should address how they would contribute to the research and/or teaching missions of our diverse and inclusive university community. Review of applications will begin immediately and continue until the position is
filled.