Project Scientist - TEEL Lab - School of Computer Science

Carnegie Mellon University’s School of Computer Science is searching for a Project Scientist! This is an excellent opportunity for someone who thrives in an interesting and challenging work environment. The Technology for Effective and Efficient Learning (TEEL) Lab at CMU is seeking a Project Scientist with demonstrated experience in designing and implementing educational experiences in emerging technology areas, especially Artificial Intelligence (AI), Machine Learning (ML), and their applications, including delivering lectures on these topics at the higher education level.

The candidate 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 machine learning, content delivery through many higher education organizations across the globe, as well as related research. A special emphasis will be put on training of the public about the use and adoption of AI/ML. The Project Scientist 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:

• Conducting research proposal process (pre-award). Advising faculty on proposal requirements and deadline planning. Developing proposal budgets. Preparing government forms and contributing administrative content to applications. Maintaining SPARCS proposal database. Working closely with Office of Sponsored Projects to ensure pre-award compliance.
• Involvement with technology-enabled learning projects primarily related to AI/ML, data engineering/science, and cloud computing. This may involve developing, deploying, and monitoring learning microservices in a cloud infrastructure, using containerization, functions as a service, and other cloud-native technologies.
• Design and develop content and occasionally deliver in-person and online lectures in one or more of the targeted areas.
• Develop 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.
• Consult with instructors about teaching and course design, especially as it relates to effective assessment practices.

You must demonstrate:

• 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.

Flexibility, excellence, and passion are vital qualities within the School of Computer Science. Inclusion, collaboration, and cultural sensitivity are valued competencies at CMU. Therefore, we are in search of a team member who can effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work.

Qualifications:

• Bachelor’s Degree Required
• Master’s degree in Artificial Intelligence, Computer Science, or related technical discipline or equivalent work experience, preferably from a university environment preferred
• Equivalent experience and/or education may be considered in lieu of degree
• Demonstrated track-record of applying rigorous quantitative and/or qualitative research methods to empirically study a research question
• Strong background in applied machine learning, natural language processing, and data science.
• Familiarity with the legal regulation of technology
• 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

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.

Requirements:

• Successful Background Check

CMU’s COVID-19 Vaccination Requirements: As a condition of employment, Carnegie Mellon University requires all staff and faculty working in the United States to be fully vaccinated, including a booster when eligible, against COVID-19. Prior to commencement of employment, new hires in the United States must provide proof of vaccination or obtain an approved exemption. (Exemptions may be requested for medical reasons or for religious or strong moral or ethical conviction.) Those granted an exemption must comply with all applicable COVID-19 mitigation requirements, including use of facial coverings, daily self-assessment and weekly Tartan Testing.

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