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

UNC-Chapel Hill School of Data and Information Sciences; Chapel Hill (NC); Presencial; USD 140 000 - 190 000; Tempo integral

Resumo da oferta

UNC-Chapel Hill's School of Data and Information Sciences invites applications for an open-rank tenure-track faculty position in the Division of Data Science and Society. The appointment will contribute leadership in AI/ML frameworks and data science methods for large-scale neuroscience and behavioral data, with translational impact.

We seek candidates with a Ph.D. or MD and a strong record in interdisciplinary research, teaching at undergraduate and graduate levels, and a vision for externally

Qualificações

• Ph.D. or MD with AI/ML, data science, CS, statistics, or related field.
• Strong record in interdisciplinary research and teaching.
• Ability to secure external funding and lead translational efforts.

Responsabilidades

• Develop and sustain an externally funded research program.
• Lead and collaborate across departments on neuroengineering initiatives.
• Teach and supervise undergraduate and graduate courses in AI/ML and data science.

Conhecimentos

Artificial intelligence

Machine learning

Data science

Statistics

Computational neuroscience

Biomedical engineering

Interdisciplinary collaboration

Formação académica

Ph.D. or MD

Descrição da oferta de emprego

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