Assistant/Associate Professor of Data Visualization

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Assistant/Associate Professor of Data Visualization

Tenure-Track Appointment 

School of Art, Media and Technology

Parsons School of Design 

Start date: July 1, 2025

Parsons School of Design, a college of The New School, acknowledges the ancestral and traditional territories of The Lenape People on which our faculty, staff and students work, learn, and create. We recognize that New York City has the largest urban Indigenous population in the United States. 

We invite candidates for a tenure-track appointment at the rank of Assistant or Associate Professor of Data Visualization in the School of Art, Media, and Technology (AMT) beginning July 1, 2025. 

We seek qualified candidates who consider themselves creative practitioners in the context of Data Visualization and Machine Learning. Candidates should have knowledge across contemporary approaches, concepts, techniques, and critical issues as they pertain to AI-based research and practice such as large language models, deep learning, classification, clustering, and regression, including cloud-based computing platforms and services to facilitate learning in the classroom. For this position, Parsons seeks a transdisciplinary artist/designer/researcher/technologist who is a pathbreaking practitioner with a clear engagement of critical theory. In this position, the faculty member would find and generate rich opportunities and vantage points to intersect across disciplines at Parsons and across The New School, an institution that actively seeks and supports interdisciplinarity. The ideal candidate presents experience and/or a clear vision for developing a new pedagogy for data visualization and machine learning as AI technologies and design practices undergo rapid transformations.

The New School is strongly committed to diversity and inclusion in the workplace and particularly seeks applications from members of underrepresented groups, as well as candidates who share this commitment. 

RESPONSIBILITIES

The work of this faculty member is divided between (1) teaching, (2) scholarship or professional/creative practice, and (3) university service. The standard teaching load is five courses––or the equivalent––per academic year. Within their field of expertise, the faculty member will be expected to teach undergraduate, including First Year, as well as graduate courses, to majors and non-majors. They will hold regular office hours, and participate in extracurricular teaching activities such as critiques, review panels, thesis supervision, independent study, and advising. University service includes program, Parsons, and New School assignments on committees and task forces, and as program directors or associate directors with a reduced teaching load in graduate and undergraduate programs, including the undergraduate First Year. All faculty are expected to be engaged with scholarship or professional/creative practice at a level commensurate with their faculty rank.

 

MINIMUM QUALIFICATIONS

  • An MS, MFA, or alternative terminal degree, in a field related to the focus of the position, or equivalent professional or creative practice experience.

  • Active/current professional practice or creative/critical scholarship that demonstrates significant creative and professional achievement in the domains of data visualization, data analysis, and machine learning.

  • Candidates seeking a position at Associate level must demonstrate equivalent teaching, research/practice experience, service and successful completion of academic review.

  • Evidence of demonstrated interest in/building the ability to mentor and support students from diverse backgrounds, to develop and nurture the individual student’s abilities, and a strong commitment to progressive education. This evidence can be in a candidate’s teaching, research, scholarship, professional/creative practice, or other experience.

  • Strong interest in working collaboratively across Parsons and the University, and have a record of working well with people from diverse cultural backgrounds, professional training, and aesthetic sensibilities.

  • Ability to work effectively as part of a team, as a collaborator or lead.

  • Evidence of a commitment to diversity and inclusion (in classroom, campus, community) in teaching, research, scholarship, professional/creative practice, or other experience.

  • Evidence of demonstrated interest in/building the ability to mentor and support students from diverse backgrounds, to develop and nurture the individual student’s abilities, and a strong commitment to progressive education. This evidence can be in a candidate’s teaching, research, scholarship, professional/creative practice, or other experience.

 

PREFERRED QUALIFICATIONS

  • Experience teaching at college, university, community-based, and/or secondary education level with evidence of engagement with course and syllabus development/planning.

  • Experience in higher education academic setting, with a working knowledge of curriculum development, student support, and management.

  • Experience teaching English language learners, students from low income backgrounds, and first generation college students.

  • University-level teaching that includes a combination of studios, seminars, and tutorials, at the undergraduate and graduate levels.

  • Experience and a vision on how to contribute to administrative service and program leadership.

 

WORK MODALITY

On-Campus Position: Faculty are expected to work on-campus due to the nature of the work in accordance with the University policies as set forth in the Full-Time Faculty Handbook. #LI-ONSITE

SALARY RANGE

Assistant Professor = $85,000 - $100,000

Associate Professor = $100,000 - $120,000

PRIORITY APPLICATION DEADLINE: December 1st, 2024

SPECIAL INSTRUCTIONS TO APPLICANTS

To apply, please submit:

  • A current CV. 

  • A cover letter: 1-2 pages summarizing experiences as related to the requirements of this job description.

  • A teaching statement: 1-2 pages describing artistic/design/research practice and teaching philosophy. Please include in the statement an articulation of your approach to inclusive pedagogy and demonstrated evidence of commitment to equity, inclusion and social justice.

  • 1 sample syllabus with assignments.

  • Names and contact information for three professional references.

  • Work samples demonstrating the applicant's creative work related to the focus of the position, including up to 20 digital images, time-based media, or links to online documentation.

  • Work samples demonstrating the applicant’s technical work, including publications, projects, and code repositories related to the focus of the position,(e.g. Github, Gitlab).

  • Samples of Student Work related to the focus of the position, (3-5 examples).

Long-listed candidates will be asked to provide:

  • Up to 10 creative, research, or professional practice projects 

  • 3–5 examples of student work mentored by the candidate

Please visit www.newschool.edu/parsons/academics for a full list of programs.

We look forward to receiving your application!

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Tags: Classification Clustering Data analysis Data visualization Deep Learning GitHub GitLab LLMs Machine Learning Research Teaching

Perks/benefits: Career development Equity / stock options Team events

Region: North America
Country: United States

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