AI Health Postdoctoral Associate

This Position is Grant Funded

School of Medicine Established in 1930, Duke University School of Medicine is the youngest of the nation's top medical schools. Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental scientific discoveries to improve human health locally and around the globe. Composed of more than 2,500 faculty physicians and researchers, more than 1,300 students, and more than 6,000 staff, the Duke University School of Medicine along with the Duke University School of Nursing, Duke University Health System and the Private Diagnostic Clinic (PDC) comprise Duke Health. a world-class academic medical center. The Health System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Primary Care, Duke Home and Hospice, Duke Health and Wellness, and multiple affiliations.

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, genetic information, gender, gender identity, national origin, race, religion, sexual orientation, or veteran status.

Duke 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.

Essential Physical Job Functions: Certain jobs at Duke University and Duke University Health System may include essentialjob functions that require specific physical and/or mental abilities. Additional information and provision for requests for reasonable accommodation will be provided by each hiring department.