Post Doctoral Fellow

Description

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), design of features that enable learning research, and pursue their own research agenda in the context of our platform, courses, and learning and teaching community. 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 design and development of training in emerging technologies such as AI, ML and Cloud based development. 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 AI/ML and cloud computing areas such as; cloud native application development, devops, and data science. This may involve developing, deploying, and monitoring learning microservices in a cloud infrastructure, using containerization, functions as a service, and other cloud-native technologies, or projects about ETL processes, data science applications, recommender systems, etc..

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 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.

The fellow will be expected to contribute to research projects that extend understanding of learning science, using the data, courses, and platform of the Sail() ecosystem. The research is expected to be centered around topics such as analyzing student behavior and performance, or effects of various interventions taken by an instructor or the system, as well as effective AI-powered methods for workforce development.

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. 

Qualifications

• A Ph.D. in Artificial Intelligence, Computer Science or a related field.
• Demonstrated research record in AI/computer supported education research and/or educational data mining research at international level.
• Demonstrated track-record of applying rigorous quantitative and/or qualitative research methods to empirically study a research question.
• 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 applications of AI and particularly large language models in educational settings.
• Experience with web service development frameworks.
• Backend development with Java and Python, particularly using Flask, Django and FastAPI.
• Experience with RESTful web services.
• Experience with SQL and NoSQL databases.
• Experience developing and managing CI/CD pipelines.
• Experience building, deploying, monitoring and troubleshooting containerized microservices using Docker, Kubernetes and Helm.

Equal Employment Opportunity Statement

Carnegie Mellon University is an equal opportunity employer. It does not discriminate in admission, employment, or administration of its programs or activities on the basis of race, color, national origin, sex, disability, age, sexual orientation, gender identity, pregnancy or related condition, family status, marital status, parental status, religion, ancestry, veteran status, or genetic information.  Furthermore, Carnegie Mellon University does not discriminate and is required not to discriminate in violation of federal, state, or local laws or executive orders. Consistent with this commitment, Carnegie Mellon will no longer be requiring or considering applicant diversity statements. If you are interested in this position and have not yet submitted a diversity statement, please do not do so. If you have already submitted a diversity statement, please know that any diversity statements submitted by applicants for this opportunity will not be considered in the hiring decision.