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The Zikry Lab at UNC-Chapel Hill is seeking a highly motivated Postdoctoral Research Fellow to join our group at the intersection of statistical methodology, machine learning, and biomedical data science. Our research develops rigorous and interpretable methods for high-dimensional biomedical data, with applications spanning cancer genomics, neuroscience, and precision medicine. The postdoctoral fellow will join a collaborative, interdisciplinary environment within the School of Data and Information Sciences, with opportunities to work with researchers across the UNC scientific community in units such as the Computational Medicine Program and the Lineberger Comprehensive Cancer Center.

The postdoctoral fellow will play a central role in advancing new statistical and machine learning methodology. Areas of focus include (but are not limited to):
* Clustering and unsupervised learning
* Dimension reduction and manifold learning
* High-dimensional inference and feature selection
* Generative modeling and digital twins
* Reliability and interpretability of ML methods

The postdoctoral researcher will be responsible for teaching at most one class per semester (an existing 100-level data science course with lecture and evaluation material provided). Based on teaching needs, this may be changed to one class per academic year.

Experience in statistical modeling and biomedical data analysis is a plus. Evidence of research productivity (publications, presentations, software) is preferred.