Postdoctoral Position in Statistical Machine Learning and Oceanography Data Modeling

The University of California, Santa Cruz is inviting applications for a postdoctoral researcher to join an interdisciplinary project at the intersection of oceanography, statistics, and machine learning. The position is supervised by Dr. Paul A. Parker and Dr. Sangwon Hyun, and involves collaboration with the University of Washington. The research focuses on developing and applying novel statistical machine learning methods for dependent, high-dimensional marine flow cytometry datasets, with the goal of advancing both AI/statistics methodology and marine microbial ecology. The successful candidate will gain interdisciplinary training, contribute to open-source software, and help develop next-generation tools for analyzing complex dependent data with broad applicability beyond oceanography. The project offers a collaborative environment and the opportunity to make fundamental discoveries in marine science. Applicants should have a PhD (completed or near completion) in Statistics or a closely related field, with demonstrated interest or experience in real-world datasets. Required expertise includes at least one of the following: spatial or spatio-temporal modeling, Bayesian hierarchical modeling, deep learning or neural networks, statistical machine learning, high-dimensional data analysis, or computational statistics. Strong programming skills in R or Python are essential. To apply, candidates should email a cover letter, CV, and contact information for three references to Dr. Sangwon Hyun and Dr. Paul A. Parker, using the subject line 'Postdoc Application'.