Postdoctoral fellowship at Harvard Biostatistics
Oct 26, 2022
Postdoctoral fellowship with Jeff Miller at Harvard Biostatistics
DESCRIPTION
Applying for this role is straight forward Scroll down and click on Apply to be considered for this position.
This is a postdoctoral position developing statistical methods for finding patterns in complex biomedical data, working with Jeff Miller in the Department of Biostatistics at the Harvard T.
H. Chan School of Public Health. Models and methods of interest include hierarchical regression models, latent factorization models, nonparametric Bayesian models, models for sequential data, mixture models, machine learning algorithms, and robustness to model misspecification.
This postdoctoral position will involve working with Dr. Miller and collaborators to develop statistical methods and software tools for analyzing high-dimensional biomedical data from cancer genomics and clinical applications.
QUALIFICATIONS
Doctoral degree in Statistics, Biostatistics, Computer Science, Applied Math, or a related field. Advanced expertise in Bayesian statistics and machine learning is essential.
Strong programming skills are required (e.g., in Julia, Python, R, C++). Experience with genomics data is a plus.
Primary author on at least one publication in a leading peer-reviewed journal.
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