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

Association for Computing Machinery (MY); Chapel Hill (NC); On-site; USD 120,000 - 170,000; Full time

Job summary

The University of North Carolina at Chapel Hill invites applications for an open-rank tenure-track faculty position in the Division of Data Science and Society (DSS) as part of the neuroengineering cluster hire initiative. We seek a leader in AI/ML and data science to translate neural and behavioral data into clinically actionable insights. Candidates should have a Ph.D.

and/or M.D. and demonstrate a strong engagement in interdisciplinary collaboration, teaching, and translation to human health,

Qualifications

• Ph.D. and/or MD with expertise in AI/ML, data science, computer science, statistics, computational neuroscience, biomedical engineering, or related field.
• Strong record of scholarly contributions and potential for securing external funding.
• Experience teaching at undergraduate and graduate levels and supervising students.

Responsibilities

• Develop and sustain an externally funded research program in brain function and neuroengineering.
• Collaborate across disciplines within the neuroengineering cluster to advance translation to human health.
• Contribute to teaching, mentoring, and curriculum development at undergraduate and graduate levels.

Skills

Research leadership

Interdisciplinary collaboration

Teaching and mentorship

Data science and AI

Education

PhD or MD in related field

Job 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.

The applicants must have a Ph.D. and/or MD with expertise in artificial intelligence/machine learning, data science, computer science, statistics, computational neuroscience, biomedical engineering, or a related field that applies AI and data science techniques.

Preferred applicants will have a strong research record, evidence of interest in developing, teaching, and supervising courses at the undergraduate and graduate levels, and an aptitude in working collaboratively in interdisciplinary research. Research with a focus on machine learning and statistical inference for large-scale, multi-modal neural data is preferred. Expertise in areas such as computational modeling of cognition and behavior, brain-computer interfaces, closed-loop neuromodulation, neuroimaging, and explainable and interpretable AI is preferred. Additionally, candidates must be able to engage with researchers, clinicians, professionals, and stakeholders from diverse disciplines. A record of or the potential to secure external funding to support research projects is strongly preferred.

For additional information about this position, please contact us at [e-mail]. Additional information about the School of Data and Information Sciences (SDIS) can be obtained at our website at https://sdis.unc.edu/.

The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, race, national origin, religion, sex, sexual orientation, or status as a protected veteran.