Mathematics Education Research Postdoctoral Fellow

Postdoctoral Researcher

The National Strategic Planning & Analysis Research Center (NSPARC) at Mississippi State University is a trusted source for inspired research, advanced analytics, and software architecture and development. NSPARC conducts interdisciplinary work across workforce and economic development, education, health, human services, corrections, and related public-interest domains.

NSPARC seeks a highly motivated postdoctoral researcher to join an interdisciplinary team conducting applied research. The successful candidate will work with combinations of structured and unstructured data, including tabular and administrative records, longitudinal and time-series data, text, images, and other sensor or digital data, and translate research questions into reproducible analyses, validated models, scholarly products, and decision-support tools. The candidate will also be expected to design, develop, and evaluate artificial intelligence and machine learning methods for complex, multimodal datasets.

A central expectation of the position is to work closely with NSPARC research faculty and staff to contribute to the Center's research portfolio through the development of new research ideas, preparation of research proposals and grant applications, and writing peer-reviewed publications. The candidate will also be encouraged to explore emerging research directions, help formulate research questions, and contribute to collaborative and interdisciplinary projects. The role is well suited to a researcher who can move fluently from research question formulation and exploration analysis to model development, rigorous evaluation, interpretation, and communication. The candidate will work closely with research faculty, scientists, software engineers, data professionals, and students to conduct interdisciplinary research, and explore emerging research directions, while demonstrating initiative and intellectual independence.

Please see Staff Compensation Structure or Skilled Crafts and Service Maintenance Compensation Schedule for salary ranges. Scholarly research and publication: Work with research faculty to formulate research questions, conduct rigorous and reproducible research, and contribute to peer-reviewed journal and conference publications.

Research proposal development: Support research faculty in developing competitive research proposals and grant applications, including literature reviews, problem formulation, methodological design, preliminary analyses, and preparation of technical content.

Research exploration and innovation: Explore emerging AI/ML methods, research problems, and application areas; identify promising research directions and contribute ideas that can lead to new studies, publications, and collaborative research initiatives.

Identify and review relevant research funding opportunities from federal agencies such as the National Science Foundation (NSF), Department of Energy (DOE), National Institutes of Health (NIH), and other public or private sponsors; work with NSPARC research faculty to assess alignment with the Center's research capabilities and priorities and help develop potential research directions in response to appropriate funding opportunities.

Multimodal research: Develop AI/ML approaches that integrate and analyze tabular, time-series, textual, image, and other data modalities.

Data engineering: Acquire, clean, harmonize, link, transform, document, and quality-check large and heterogeneous datasets; build reusable and auditable data pipelines.

Conduct temporal and longitudinal analyses, including forecasting, anomaly detection, sequence modeling, and appropriate validation under temporal dependence.

Computer vision: Language and multimodal AI: Build and assess natural language processing, large language model (LLM), vision-language model (VLM), embedding, retrieval-augmented generation, and multimodal fusion workflows when appropriate to project goals.

Research translation: Statistical and descriptive analysis: Conduct rigorous descriptive and traditional statistical analyses, including data summarization, estimation, hypothesis testing, regression, analysis of variance, and other appropriate inferential methods; Provide comprehensive research support for interdisciplinary projects, contribute to research and project planning, data analysis, development of research reports and other deliverables, and collaborate effectively with internal and external researchers and project teams.

A PhD in Computer Science, Artificial Intelligence, Machine Learning, Electrical and Computer Engineering, Statistics, Applied Mathematics, or a closely related field.

Experience with multimodal learning, representation learning, data fusion, or joint modeling across structured data, time series, text, images, video, audio, or sensor data.

• Experience developing computer vision systems using convolutional neural networks, vision transformers, vision foundation models, or related architectures.
• Experience working with administrative, education, workforce, economic, health, geospatial, or other public-sector data.

A strong publication record and demonstrated ability to contribute to manuscripts, grant proposals, or sponsored research deliverables.

Demonstrated ability to formulate research questions, review and synthesize relevant literature, design rigorous experiments, and interpret research findings.

• Demonstrated ability to communicate research methods and findings through scholarly manuscripts, technical reports, presentations, or other research products.
• Ability to work effectively with research faculty and interdisciplinary teams in developing research ideas, conducting studies, and contributing to publications and research proposals.
• Strong proficiency in Python and common ability to write clear, efficient, maintainable, and reproducible research code.
• Demonstrated capability in data engineering, exploratory data analysis, feature engineering, statistical reasoning, and validation of large or complex datasets.
• Ability to work with multiple data modalities and select methods that fit the research question, data-generating process, and operational constraints.
• Ability to work independently, manage priorities and deadlines, and contribute effectively within an interdisciplinary and broad research environment.
• Commitment to research integrity, responsible AI, data privacy, security, reproducibility, and ethical use of sensitive or restricted data.

Work is performed primarily in a comfortable indoor office or computing environment and frequently involves sitting, communicating, hearing, handling objects, and viewing information in print or electronically. Occasional overnight travel may be expected.

Applicants should complete the online application at explore.A cover letter describing research interests and alignment with the position;

Mississippi State University is an equal opportunity institution. Discrimination is prohibited in university employment, programs or activities based on race, color, ethnicity, sex, pregnancy, religion, national origin, disability, age, sexual orientation, genetic information, status as a U.S. veteran, or any other status to the extent protected by applicable law. Questions about equal opportunity programs or compliance should be directed to the Office of Civil Rights Compliance, 231 Famous Maroon Band Street, P.In compliance with the ADA Amendments Act (ADA), if you have a disability and would like to request an accommodation in order to apply for a position with Mississippi State University, please contact the Department of Human Resources Management at tel: View phone number on click.appcast.io or View email address on click.appcast.io.

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