The School of Data Science and Society (SDSS) at UNC-Chapel Hill is excited to announce an open rank tenure and/or tenure-track faculty hiring initiative for several positions to bolster research and innovation in the emerging field of Data Science. While we welcome applications from all exceptional candidates whose expertise in the field relies on a human-centric approach to researching the entire data life cycle, we are particularly interested in applicants who conduct research at the intersection of the rapidly evolving fields of Artificial Intelligence (AI) and Health (broadly defined). SDSS aims at creating important ways to improve the wellbeing of individuals and communities using Data Science, and we recognize the immense potential of AI technologies in transforming health at all scales. Based on the applicant's interests, a secondary appointment in a related UNC academic unit may be possible.

We are seeking exceptional researchers that work in or across the following of SDSS's research pillars:

* Data: Methods of collection, storage, dissemination, and translation of data into actionable information
* Algorithms and Models: Computational and statistical tools to enable researchers and stakeholders to discover, create, analyze, present, synthesize, and consume data
* Applications: Sound and creative deployments of both data and models to advance interdisciplinary domains of knowledge, as well as offer solutions to pressing social problems.
* Social Impact: The study of unintended consequences and ethical questions raised by the ways in which data is used to address some of society's most pressing issues.

SDSS seeks a range of experts that excel in foundational areas of AI methodologies, machine learning, data science, and computational analysis, coupled with a strong background in one or more of the following disciplines: medicine, clinical research, pharmaceuticals, public health, mental health, health disparities, health administration, health informatics, electronic medical records, health policy and advocacy, health law, nutritional sciences, exercise science, health promotion, occupational health and safety, or health communications. Researchers with a focus on the ethical implications of AI in health and study areas such as data privacy, algorithmic bias, informed consent, and AI model transparency are also encouraged to apply.

Responsibilities:
1. Conduct Research: Engage in high-quality interdisciplinary research in data science and society by developing and implementing new methodologies, algorithms, and models. Identify research topics and secure external funding to support research endeavors. Publish research findings in top-tier journals and present work at national and international conferences.

2. Teach and Mentor: Teach undergraduate and graduate courses in data science, data analytics, machine learning, statistics and related areas. Mentor and supervise graduate students and provide guidance to undergraduate researchers. Contribute to curriculum development in data science programs.

3. Collaborative Engagement: Participate actively in interdisciplinary collaborations within the School of Data Science and Society, as well as with other relevant departments and research centers. Contribute to the growth and development of the school by collaborating with industry partners, professional organizations, and community stakeholders.

4. Service: Engage in service duties within the university, including committee work and administrative responsibilities. Contribute to the academic community through involvement in professional societies, reviewing manuscripts for journals, and organizing scientific events.

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 data science and its applications in addressing societal challenges is preferred. Expertise in areas such as AI/machine learning, data analytics, social network analysis, or data ethics is preferred. Additionally, candidates must be able to engage with researchers, professionals, and stakeholders from diverse disciplines. A record of or the potential to secure external funding to support research projects is preferred.