The University of Minnesota (UMN) Learning Informatics Lab seeks candidates to fill two Post-Doctoral Associate positions. The Lab is an interdisciplinary research lab based in the College of Education and Human Development and dedicated to advancing and applying data science and informatics techniques to educational data in order to address pressing challenges in K-12 education.
These positions are part of a new project in Educational Data Mining and Learning Engineering funded by Schmidt Futures (https://schmidtfutures.com) and in collaboration with Infinite Campus. Schmidt Futures funds interdisciplinary networks for early-stage talent and advanced computing platforms to accelerate research. Infinite Campus is a Minnesota-based company that builds and deploys student information and learning management systems for K-12 education. The post-doctoral associates will be full-time employees of the University of Minnesota, and will also join the Visiting Scholars program at Infinite Campus.
The goal of this two-year grant is to develop new, cutting-edge research projects that will advance learning engineering, learning analytics, educational data mining, and cognitive science. The specific projects will be developed by the post-doctoral associates with guidance from U of M faculty and Infinite Campus staff. Projects can take on areas such as personalized learning, proficiency estimation, predictive learning analytics, adaptive assessment, curriculum recommendation, and promotion of fairness and transparency in learning analytics. Projects are encouraged to address pressing challenges in K-12 education, from better matching students with learning paths that meet their needs to addressing achievement gaps.
The post-doctoral associates will work closely with a team of faculty at the Learning Informatics Lab, led by Prof. Bodong Chen (Learning Technologies), and including Prof. Joseph Konstan (Computer Science and Engineering) and Prof. Sashank Varma (Computer Science and Psychology, Georgia Tech), along with other faculty members in the Lab (https://innovation.umn.edu/informatics/). They will work in partnership with teams at Infinite Campus with expertise in data science, creating data science solutions to novel educational problems, building machine-learned products, and developing applications for K-12 teaching and learning. This position may perform job responsibilities related to Infinite Campus customer data, which may be subject to a more thorough criminal background check to include, but not limited to, fingerprints, outside the standard screening. If the position performs job responsibilities directly related to specific customer(s), employee is required to pass the specified criminal background check; meeting the requirements of the customer contract.
The post-doctoral associates should be committed to producing original research and publishing their work in highly ranked conference proceedings and journals (as appropriate). The PIs and the Learning Informatics Lab are committed to the professional development of the post-doctoral associates, and will provide resources to support professional development including participation in professional conferences.
Research & Project Management (100%)
Conceptualize, design, and implement computational research projects that make use of Infinite Campus’ massive Student Information System (SIS) and Learning Management System (LMS) data.
Work alongside Lab faculty to design, plan, coordinate and implement logistical aspects of projects: Track progress, facilitate communication, and ensure organization both within and across research projects.
Work closely with teams at Infinite Campus to access their massive SIS and LMS data to address research questions.
Manage, institute, and document procedures for research planning, data analyses, and reporting at the University of Minnesota.
Lead and assist with the preparation of research articles, reports, grants and related materials.
Disseminate research findings at academic conferences and journals.
A Ph.D. in data science, computer science, machine learning, statistics, cognitive science, learning analytics, or an allied discipline.
A strong technical background with demonstrated experience developing computational tools and/or applying data science methods to large data sets.
A desire to use data science approaches to address challenges and problems in education.
Proficiency with managing complex data sets and quality control procedures.
Strong organizational and communication skills.
Strong professional writing skills, including research reports, peer-reviewed research articles, or other print and electronic publications.
Experience in collaborating as a member of a larger research team.
Ability to work well with diverse populations.
Internal Number: 336799
About University of Minnesota, Twin Cities
The University of Minnesota, founded in the belief that all people are enriched by understanding, is dedicated to the advancement of learning and the search for truth; to the sharing of this knowledge through education for a diverse community; and to the application of this knowledge to benefit the people of the state, the nation, and the world.