Duke University, Biostatistics & Bioinformatics

Position ID:Duke-Biostatistics & Bioinformatics-PD237224 [#25963]
Position Title: AI Health Postdoctoral Associate - Biostatistics & Bioinformatics
Position Type:Postdoctoral
Position Location:Durham, North Carolina 27710, United States [map] sort by distance
Subject Areas: Medicine / Artificial Intelligence, Machine Learning and Autonomy
Statistics / Machine Learning
Biostatistics
Appl Deadline:none (posted 2023/09/27)
Position Description:    

AI Health Postdoctoral Associate 

The Berchuck lab at Duke University (Durham, NC, USA) is looking for a highly motivated Postdoctoral Associate in the fields of applied Bayesian modeling and machine learning using large longitudinal biomedical data, including electronic health records and mobile health data. The position will be funded by Samuel I. Berchuck, PhD who holds appointments in the Departments of Biostatistics & Bioinformatics and Statistical Science and is a faculty affiliate of Duke AI Health. The appointment is for 2 years, starting October 1, 2023, or a later date, and may be renewed for 1 year. The postdoc will have the opportunity to be affiliated with Duke AI Health as a Duke AI Health Postdoc. 

OVERVIEW. The successful applicant will use tools from statistics, biostatistics, and machine learning to analyze and model rich longitudinal datasets from patients with chronic diseases, including glaucoma and cancer. Possible projects include (i) developing Bayesian semi-supervised inference algorithms for predicting psychosocial distress in patients with glaucoma, (ii) identifying pain trajectories in cancer survivors using Bayesian latent class models, and (iii) developing scalable Bayesian inference algorithms for high-dimensional longitudinal settings. All three of these projects will require a certain degree of applied methods development. 

QUALIFICATIONS. The successful applicant has a doctorate in biostatistics, statistics, machine learning, computer science, or a related discipline. The position requires proficiency in Bayesian inference techniques (e.g., MCMC, Stan), longitudinal data analysis, and modern machine learning approaches. Extensive experience with real-world (e.g., electronic health records) data and advanced statistical computing skills are required. The successful applicant demonstrates great attention to detail, works independently, takes initiative, has excellent written and verbal communication skills, and performs well in an interdisciplinary environment at the interface between data science and clinical research. The successful candidate is expected to have a track record of first-author publication in peer-reviewed journals. 

APPLICATION. Interested applicants should submit the following documents: 
• Cover letter describing research interests and career goals (2 pages or less) 
• Curriculum vitae (4 pages or less) 
• Copies of 1-2 relevant first-author publications 
• A list containing the contact information for 3 references 


Completed applications will be reviewed on an ongoing basis until the position is filled, with priority given to applications submitted prior to January 1, 2024.


Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status.

Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas-an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values.


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Web Page: https://biostat.duke.edu/