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Open Rank - Neuroengineering Cluster- Assistant/Associate/Full Professor

University of North Carolina- Chapel Hill

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At a glance

Compensation
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Location
NC-Chapel-Hill, NC
Work Authorization
Not specified

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Job overview

The University of North Carolina Chapel Hill seeks an open‑rank tenure‑track faculty member for its Neuroengineering Cluster within the Division of Data Science and Society. The role focuses on leading machine‑learning, statistical, and AI research on large‑scale neural and behavioral data, fostering interdisciplinary collaboration, and translating discoveries into clinical health benefits.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningStatistical InferenceNeural Data IntegrationComputational ModelingNeuroimaging AnalyticsAdaptive NeuromodulationFoundation ModelsData GovernanceArtificial Intelligence

Full job description

Employment Type: Permanent Faculty

Vacancy ID: FAC0006079

Salary Range: Commensurate with Education and Experience

Position Summary/Description:

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 analytics, adaptive neuromodulation, foundation models for neural and behavioral data, and related approaches that advance understanding of brain function and support neurotechnology development. A translational emphasis (such as clinical decision support or neurotechnology deployment) that can position this work to deliver direct, measurable benefits to human health is also desirable. Faculty in this cluster will be recruited with a strong commitment to team science, including joint appointments where appropriate, and coordinated research programs spanning devices, systems, computing, modeling, and translation. Through collaboration among faculty, students, external partners, and the clinical community, the Division of Data Science and Society in SDIS aims to translate research discoveries into tangible societal benefits. We invite you to join the DSS faculty and be part of this mission.

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