The University of Maryland College of Information Studies (UMD’s iSchool) invites applications for a full-time lecturer in Data Visualization and related areas. As a lecturer in the iSchool, you will work closely with undergraduate and graduate students by teaching three classes per semester (fall and spring), participate in review and development of program and course curricula, and actively participate in the life of the college and university as a full member of the faculty.
The position is open rank: hiring can happen at any level depending on seniority (lecturer, senior lecturer, principal lecturer).
The focus of this position includes:
- Data visualization — visualization, interactive visualization, information visualization, scientific visualization;
- Visual analytics — visual analysis, progressive analytics, visual reasoning, analytical reasoning, immersive analytics; and/or
- Visual data exploration — exploratory data analysis, graphical inference, statistical graphics
Possible course assignments include Introduction to Data Visualization, Data Visualization, Visual Analytics, Decision-Making for Information Science, and Big Data Analysis & Visualization. While these areas are of particular interest, candidates with expertise and interest in any data visualization topics are encouraged to apply.
Successful candidates will have a graduate degree in information science, computer science, visual design, or a related area (Ph.D. preferred but not necessary); experience preparing and delivering interactive educational experiences (university teaching experience preferred); and excellent written and oral communication skills. Rank, salary, and contract terms are flexible and will be determined based on candidate experience and needs. For best consideration please provide a letter of interest, CV or resume, contact information for three references, and a personal statement/teaching statement by January 31, 2022.
To submit an application or for more information about the UMD iSchool, the position, or compensation see https://ejobs.umd.edu/postings/91031
