Postdoctoral Research Associate

Position Function:

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 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.

Salary Grade

UC

Please see Staff Compensation Structure or Skilled Crafts and Service Maintenance Compensation Schedule for salary ranges. For salary grade UC, these positions are "Unclassified" and salary ranges are determined by the hiring department.

Essential Duties and Responsibilities:

• 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.
• Funding opportunity exploration: 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.
• Time-series modeling: Conduct temporal and longitudinal analyses, including forecasting, anomaly detection, sequence modeling, and appropriate validation under temporal dependence.
• Computer vision: Develop and evaluate models for image classification, object detection, segmentation, representation learning, and related vision tasks.
• 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.
• Model evaluation: Design rigorous experiments; select meaningful baselines and metrics; assess generalization, calibration, uncertainty, robustness, bias, fairness, and error patterns.
• Research translation: Convert analytical results into clear reports, visualizations, presentations, technical documentation, and actionable recommendations for technical and nontechnical audiences.
• 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; clearly interpret assumptions, effect sizes, uncertainty, and practical significance.
• Collaboration: 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.

Additional duties may be assigned consistent with the knowledge, skills, and abilities required for the position.

Minimum Qualifications

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

Preferred Qualifications

• Hands-on experience with PyTorch, TensorFlow, scikit-learn, or comparable machine-learning frameworks.
• 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 adapting, fine-tuning, evaluating, or deploying LLMs and VLMs; familiarity with prompting, embeddings, retrieval-augmented generation, parameter-efficient tuning, and multimodal evaluation.
• Experience with forecasting, temporal deep learning, or longitudinal modeling.
• 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.

Knowledge, Skills, and Abilities

• 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.
• Working knowledge of supervised and unsupervised learning, deep learning, model selection, hyperparameter optimization, and appropriate experimental design.
• Ability to work with multiple data modalities and select methods that fit the research question, data-generating process, and operational constraints.
• Strong written and oral communication skills, including the ability to explain technical methods, assumptions, limitations, and results to audiences.
• 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.

Working Conditions and Physical Effort

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. The position requires limited lifting of files and records. Work may involve externally imposed deadlines, changing priorities, interruptions, coordination of unrelated activities, and occasional conflict-resolution or other stressful interactions. Occasional overnight travel may be expected.

Restricted Clause

Position is contingent upon continued availability of funding.

Equal Employment Opportunity Statement

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.O. 6044, Mississippi State, MS 39762, View phone number on click.appcast.io.

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