Assistant Professor of Philosophy with the School of Data Science
The Department of Philosophy at the University of North Carolina at Charlotte invites applications for a tenure-track position, rank Assistant Professor, beginning Fall 2022. AOS: Ethics and Data Science, with a strong preference for non-ideal approaches and for research that is significantly grounded in philosophical traditions traditionally underrepresented in the field (e.g., feminist, queer/trans, non-Western, African-American, Indigenous, disability studies, etc., including innovative applied work). AOC: Open. The successful candidate will have a tenure home in the Department of Philosophy, with a workload split of 70% in Philosophy and 30% in the University’s interdisciplinary School of Data Science.
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Assistant/Associate Professor, Non-Tenure Track
The School of Data Science [SDS] at UNC Charlotte is an interdisciplinary unit that is supported by the Academic Affairs’ Office of the Provost, the College of Computing and Informatics, the Belk College of Business, the College of Health and Human Services, the College of Liberal Arts and Sciences, the William States Lee College of Engineering, as well as other academic units. SDS oversees two graduate programs in Health Informatics and Analytics [HIA] and Data Science and Business Analytics [DSBA] with over 300 students enrolled. A new undergraduate degree was launched in Spring 2021 and has quickly grown to nearly 100 majors. A Ph.D. program is in the planning stage. The vision of the School of Data Science is to become a leader in ethically grounded, interdisciplinary data science and artificial intelligence research and education that serves our diverse local and global community. SDS is highly engaged with industry through our Industry Advisory Board and our annual analytics conferences.
Description of Work
The University of North Carolina at Charlotte recognizes the differentiation of mission, goals, and objectives inherent in the diversity of disciplines represented by its colleges and departments. Thus, the Job Responsibilities and Essential Functions for Non-Tenure Track Faculty should be interpreted in the context of the related departmental and collegiate teaching goals.
Teaching – Faculty responsibilities and essential functions with respect to teaching may include but are not limited to: subject matter competence, course design, course presentation, and grading student work.
Essential Duties and Responsibilities
This position will be expected to primarily teach undergraduate and graduate courses in the School of Data Science including studio-based data science courses. These studio courses are taught with two or more instructors and often include one with expertise in computing and statistics and others with expertise in social science. This position also conducts research in their fields of expertise and participates in academic service and interdisciplinary activities.
Priority is given to applicants with a focus on data science including data science education, applied AI, data mining, computer vision, ethics of AI, sports analytics, or health informatics. The ideal candidate would demonstrate expertise in cross-disciplinary and data-oriented areas as mentioned above, have a track record of publications, as well as have the ability or potential to procure competitive external funding. This position will create bridges between data science, social sciences, and humanities.
Preferred Education, Skills and Experience
Ph.D. in a field related to data science.
Experience in teaching data science, statistics, and/or computer science; knowledge and experience in statistical and data mining techniques.
Experience with querying databases and using statistical computer languages: NoSQL, Python, R, SQL, and other related languages.
Experience with course design and course presentation and experience visualizing/presenting data for stakeholders.
Experience analyzing data with third-party cloud providers.
Ability and willingness to contribute to diversity initiatives of the unit, department, college, and university.
Evidence of publication of material related to use of data mining techniques in the professional or service setting; demonstrated commitment to quality teaching at both the undergraduate and graduate levels.
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