Data-Intensive Course Developer & Instructor

Description

The Cooperative Institute for Research in the Environmental Sciences (CIRES) and the University of Colorado Earth Lab are accepting applications for a data-intensive course developer with a science background and experience programming in Python (required) and R (preferred) to develop undergraduate and graduate level courses that teach a blend of scientific programming and scientific computing workflows (version control, cloud computing, etc.), earth science and interdisciplinary collaboration. Courses created will be included in a professional graduate certificate in Earth Data Analytics - Foundations and forthcoming professional master’s program in Earth Data Analytics. This position will report to the Director of the Earth Analytics Education Initiative. Review of applications will begin on November 15, 2017, applications will be accepted until the position is filled. This will be a one-year appointment with full benefits, with the possibility of renewal after a year. 

The Earth Lab Earth Analytics Education Initiative is also invested in teaching and learning pedagogy and program assessment. The successful applicant will participate in evaluation activities including supporting development and implementation of evaluation protocols (surveys, rubrics, etc.) as well as research and publication in the area of data intensive instruction.

Duties

-Create data-intensive content for Earth Analytics courses that will be posted online (see earthdatascience.org for example course content)

-Serve as primary instructor for at least one Earth Analytics course per semester

-Assist in pedagogical research and evaluation through administering course surveys, analyzing data, and publishing on findings

-Initiate and foster relationships with industry partners to devise hands-on course projects based on real private sector needs, in order to better prepare students for careers in Earth Analytics

Minimum Qualifications:

  • Master’s degree in science with strong data-intensive component from an accredited university
  • Demonstrated teaching / course / workshop development experience at the university level
  • 2-3 years of experience working with large, heterogeneous, spatio-temporal scientific and other related datasets using GUI and non-GUI based tools
  • 3-5 years experience teaching technical scientific topics
  • Demonstrated proficiency in scientific programming, specifically Python
  • Demonstrated working knowledge of Git / Github
  • Experience with collaborative scientific workflows (e.g. Google suite, slack, etc)

Preferred Qualifications:

  • PhD in science, mathematics or engineering with strong data-intensive component from an accredited university
  • Demonstrated experience working with spatial and remote sensing data.
  • 1-5 years of teaching experience at the college level (can include experience gained during graduate studies)
  • 1-5 years of professional experience, working in sciences 
  • Demonstrated working knowledge of docker / containerized workflows
  • Demonstrated working knowledge of cloud computing (e.g. Amazon web services)
  • Demonstrated experience creating and teaching online courses
  • Demonstrated experience working with data in R
  • Interest in pursuing research in the realm of data-intensive teaching approaches (pedagogy)

 

Application Materials Required

Cover Letter, Resume/CV, List of References, Unofficial transcript(s) 

 

Apply Here