Research Assistant Professor In Data Visualization

Duties and Responsibilities

This is a non-tenure track, research-only position at the Assistant Research Professor level. The successful candidate will contribute to research and scholarship through receipt of extramural funding as well producing high-quality publications, presentations at prominent national and international academic conferences, impact as measured through citations, exhibitions, festivals, and/or national recognition as through honorific awards. Excellent communication skills, an ability to secure funding, and a collaborative predisposition are essential for this position. Although formal teaching is not part of duties, mentoring of students is required. Successful candidates will also be expected to broaden participation among members of under-represented groups as demonstrated through research, public engagement, and richness of diversity in the learning experience.

Minimum Qualifications

• Advanced degree (Masters) in Animation, Art, Computer Science, Digital Media, Information Design, or other appropriate fields. Equivalent foreign degrees are acceptable.
• Demonstrated success in securing extramural research funding.
• Strong portfolio demonstrating professional practice in digital visualization and information design (via animation, digital graphics, computer science, data analytics, etc.).
• Prior industry or entrepreneurial experiences/collaborations.
• Superior written and oral communication skills.

PREFERRED QUALIFICATIONS

• Terminal degree (e.g., Ph.D, M.F.A., etc.) in Animation, Art, Computer Science, Digital Media, Information Design or other appropriate fields. Equivalent foreign degrees are acceptable.
• Experience in a collaborative environment with a diverse team
• Evidence of serving as a mentor to students and/or as an advisor to businesses.
• Experience with technology commercialization (securing patents, startup formation, etc.).
• Desire to be a part of an experimental cohort of energetic and ambitious data science research faculty who come from different disciplines, but together can contribute to substantive paradigm shifts.
• High-quality publication or exhibition record in data visualization.