The Technology for Effective and Efficient Learning (TEEL) Lab at CMU is seeking a postdoctoral fellow who will contribute to educational research projects that collect and analyze data on student and workforce learning outcomes to inform the development and maintenance of the learning infrastructure (learning management system (LMS), auto-grading, social interaction) and design of features that enable learning research. New initiatives include the development of infrastructure and content for a large-scale governmental and industrial workforce education in cloud computing, data science, and AI/ML content delivery through a large number of higher education organizations across the globe, as well as related research. A special emphasis will be put on education of the general public about the use and adoption of AI/ML. The Postdoctoral Fellow will be a member of our team to develop, maintain, and utilize a project-based online social learning platform for workforce training at scale.

The TEEL lab develops, maintains, and evaluates a portable and interoperable online learning ecosystem that enables effective and efficient learning that leverages social interactions between students as a substantial learning resource. Furthermore, in addition to software development, the lab conducts studies of student learning and evaluates innovative approaches for incorporating social learning as a driver for developing cognitive skills and motivation through reflection, interaction, and cohort building.

Core Responsibilities Will Include

As a postdoctoral fellow in the TEEL Lab, you will be involved with technology-enabled learning projects primarily related to cloud computing, data science, and AI/ML. This may involve developing, deploying, and monitoring learning microservices in a cloud infrastructure, using containerization, functions as a service, and other cloud-native technologies.

The fellow is expected to develop content and deliver in-person and online lectures in one or more of the targeted areas. The position also involves developing appropriate metrics for assessing student learning, collecting, analyzing, and interpreting data on student learning, attitudes, and engagement, reporting on assessment data and research-based pedagogical strategies, disseminating best practices, research, and emerging developments on formative assessment, including partnering with faculty to publish assessment work. The position may also include consulting with instructors about teaching and course design, especially as it relates to effective assessment practices.

How we work in the TEEL Lab
  • Learner-centered decision making.
  • Fast-paced research-driven environment.
  • Ability to respond to urgent requests for production deployments.
  • Ability to communicate with engineers, researchers, students, and CSP partners.
  • Ability to work independently, take ownership of tasks and deliver high-quality work.
  • Effective collaboration within a team environment.
  • Effective project and time management skills.
  • A Ph.D. in a related field.
  • Demonstrated track-record of applying rigorous quantitative and/or qualitative research methods to empirically study a research question.
  • Research background in applied ML, natural language processing (NLP), or data science.
  • Demonstrated teaching experience of technical subjects, such as cloud computing or data science, to people with little to no technical background.
  • Experience securely managing and analyzing complex data sets.
  • Strong oral and written communication skills, including maintaining confidentiality.
  • Ability to work collaboratively, effectively, and professionally in settings of social and intellectual diversity.
  • Ability to successfully navigate ambiguity, balance multiple competing responsibilities, meet deadlines on time, and meticulously pay attention to detail.
  • Sensitivity to teaching and learning needs at a research university.
Preferred qualifications:
  • Experience with commercial cloud services such as Microsoft Azure, AWS or Google Cloud Platform.
  • Experience with web service development frameworks.
  • Full-stack development with HTML, CSS, Javascript, Python.
  • Experience with RESTful web services.
  • Experience with SQL and NoSQL databases.
  • Experience building, deploying, monitoring and troubleshooting containerized microservices using Docker, Kubernetes and Helm.
Application Instructions Equal Employment Opportunity Statement

Carnegie Mellon University shall abide by the requirements of 41 CFR §§ 60-1.4(a), 60-300.5(a) and 60-741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, or national origin. Moreover, these regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, national origin, protected veteran status or disability.

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