Neuroengineering Cluster- Assistant​/Associate​/Full Professor

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In July 2026, UNC Chapel Hill launched the Division of Data Science and Society within the School of Data and Information Sciences (SDIS), a division devoted to data science teaching, research, scholarship, service, and creativity. DSS’s vision is to be a leader in shaping the field of data science through an interdisciplinary and rigorous grounding in theory and methods with a human centric approach to the entire data life cycle.

The mission of DSS is to empower a diverse community of faculty conducting research in the fundamentals and/or the applications of data science. The Division is training undergraduate, graduate, and professional students to be the next generation of data science leaders with the knowledge and skills to thrive in this data-driven world. The Division will serve the state, the nation, and the world through premier data science educational programs and innovative research directed to advancing the public good with human centric and ethical applications.

The core elements of SDIS include porous borders: leveraging our low walled collaborative Carolina culture to solve major societal problems. Interdisciplinary research clusters that cross Division and School boundaries are a vital element of our Scholarly community. The School of Data and Information Sciences is focused on students and education; the emphasis is not just on data science majors but on all students becoming data literate.

The School’s culture has an open and transparent structure, governance, and business model.

The Division of Data Science and Society (DSS) at UNC-Chapel Hill’s School of Data and Information Sciences (SDIS) is excited to announce an open-rank tenure-track faculty position as part of the University’s neuroengineering cluster hire initiative. This cluster unites the Lampe Joint Department of Biomedical Engineering, the Department of Computer Science, the Department of Neurosurgery, and DSS to build a collaborative, interdisciplinary hub in neuroengineering, focused on brain-computer interfaces (BCIs), brain function imaging and interpretation, closed-loop neuromodulation, and the translation of neuroengineering innovations into improved human health.

Within this cluster, the DSS position will provide leadership in machine learning, statistical, and AI frameworks that transform complex large-scale, multi-modal neuroscience and behavioral data into clinically relevant insights, addressing core challenges of heterogeneity, dimensionality, harmonization, and data governance. This position complements cluster strengths in neuroengineering devices, real-time computing systems, and clinical translation, serving as a link between data acquisition, scientific discovery, and application.

The successful candidate will work with cluster faculty to develop and sustain an externally funded research program focused on understanding, predicting, and translating brain function into large-scale neural and behavioral data. Research areas of interest include machine learning and statistical inference for neural data, multimodal neural data integration and harmonization, computational modeling of cognition and behavior, neuroimaging…