Open Rank Professor of Data Science, Tenured / Tenure-Track

Key Skills

Cloud computing, Software Development, Data Architecture, Distributed systems

Job Description

The School of Data Science at the University of Virginia seeks applicants for multiple Open Rank Tenured or Tenure Track Professors of Data Science. The school is assembling a diverse and world-class faculty with broad expertise in data science. We are seeking candidates with a pioneering spirit, who have methodologic expertise or applied experience in one or more domains of data science. Examples include, but are not limited to, Analytics (e.g., prediction modeling, machine learning, imaging, computer vision, algorithm development, statistical methods), Data Structures & Informatics (e.g., data architecture and pipelines, database theory, bioinformatics), Data Systems (e.g., high performance computing, distributed systems, software development, tool deployment, cloud architectures), Data Communication (e.g., visualization, human-computer interaction, interpretation) and Data Policy & Ethics (e.g., representativeness, privacy, ethics of algorithmic construction and deployment). Candidates with diverse backgrounds and broad methodological expertise or industry experience in data science are especially encouraged to apply. A commitment to diversity, equity, and inclusion in data science education and research is essential for all candidates.

The School of Data Science at UVA was established in 2019 with the largest private gift in the institution’s 200-year history. The school seeks to set the standard in data-centered practice to harness the power of data to better humanity though the proper collection and use of data, and though the development of novel data methodologies and impactful applications. Faculty duties include research, teaching (in-person and online), mentoring, advising students, and service to the university and the discipline. Faculty will have the opportunity to help shape the culture of a new school, develop modern pedagogy, and grow the discipline of data science in national and international forums.

Candidates must have earned, or be on track to earn, a PhD in Data Science or a related field (e.g., STEM, social science or humanities degree with a Data Science focus) by August 2022 or appointment start date. Appointments are made in the School of Data Science, with the potential for joint or courtesy appointments in other schools as applicable. We especially encourage applications from individuals who are members of underrepresented groups, candidates conducting impactful researching on underserved populations, or candidates who have worked to broaden student access to data science careers.

Candidates for senior-level positions (Associate and Full Professor with tenure) must have a demonstrated record of excellence in research, teaching, and advising, in data science and/or closely related fields, and must have established a national/international reputation for contribution to the field in methodology, application, and impact.

Candidates for Assistant Professor (tenure-track) positions must demonstrate the potential for excellence in methodological development and scientific impact in data science or a related field and have prior experience in educational related activities.

TO APPLY:

Complete an application online and attach:

• Curriculum Vitae
• Cover Letter that addresses your fit for this position and your interest in data science.
• A teaching and research statement that describes your teaching and mentoring philosophy, and your past research endeavors and contributions. Be sure to explain, where applicable, the impact of your work in fostering diversity, equity, and inclusion in teaching, research, and service experiences. The teaching and research statement may be separate documents.
• A diversity statement that summarizes your experience with fostering diversity, equity, and inclusion goals in your research and teaching activities (please provide examples of past activities where possible).
• Contact information for 3 references (prior to appointment three recommendation letters will be required)
• If available, reviews & course evaluations from up to 3 past courses/seminars/short-courses.

Note: Application materials should be combined into a single file in the order listed above and uploaded to the resume / cv box