Teaching Assistant | Environmental Data Analysis and Visualization
Tufts Technology Services are looking to hire a fall 2018 teaching assistant for the new Environmental Studies course, ENV-170 Environmental Data Analysis and Visualization. It’s a great way to develop data analysis and visualization skills. The position requires 6 hours per week.
Duties
Attend class and provide classroom assistance during scheduled class time, hold regular office hours to assist students with their assignments and troubleshoot code issues, assist with general course maintenance and management.
Attend class and provide classroom assistance during scheduled class time, hold regular office hours to assist students with their assignments and troubleshoot code issues, assist with general course maintenance and management.
Required skills
R competence equivalent with completing an intermediate coding course, including data management with common packages, importing and exporting data, and performing statistical analysis (e.g. multivariate regression models), ability to work patiently and thoughtfully assisting students, good communication skills, and interest in learning and expanding one’s statistical software skills.
R competence equivalent with completing an intermediate coding course, including data management with common packages, importing and exporting data, and performing statistical analysis (e.g. multivariate regression models), ability to work patiently and thoughtfully assisting students, good communication skills, and interest in learning and expanding one’s statistical software skills.
Contact: kyle.monahan@tufts.edu
Day/Time: Tuesday and Thursday, 9:00AM – 10:15AM, Tisch Library, Data Lab, Medford/Somerville
How to apply
Please send your resume/CV as an attachment to the email contact above.
Course description
Provides skills in data management, study design, statistical analysis, and data visualization that are critical for those working in environmental fields through hands-on experience working with environmental datasets. Environmental data are unique in that they are often spatial in nature, containing multiple variables that interact. These types of data require a careful approach to analysis and visualization. Topics covered include best practices in data access and storage, data analysis and interpretation, and data visualization for relevant stakeholders. Prerequisite: An introductory statistics course.
Provides skills in data management, study design, statistical analysis, and data visualization that are critical for those working in environmental fields through hands-on experience working with environmental datasets. Environmental data are unique in that they are often spatial in nature, containing multiple variables that interact. These types of data require a careful approach to analysis and visualization. Topics covered include best practices in data access and storage, data analysis and interpretation, and data visualization for relevant stakeholders. Prerequisite: An introductory statistics course.
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