Postdoctoral Research Associate

Postdoctoral Research Associate

• 511305
• Main Campus - Starkville, MS
• Mississippi - Main Campus
• 192900 - nSPARC
• Professional
• Regular Full-Time 12-month
• Time-Limited Full-Time 12-Month
• Opening on: Sep 24 2026

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Position Function:

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 design, develop, and evaluate artificial intelligence and machine learning methods for complex, multimodal datasets. 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 analytical pipelines, validated models, scholarly products, and decision-support tools.

The role is well suited to a researcher who can move fluently from data engineering and exploration analysis to model development, rigorous evaluation, interpretation, and communication. The candidate will collaborate with research faculty, scientists, software engineers, data professionals, and students, 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:

• 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, manuscripts, proposals, 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: Contribute to interdisciplinary project planning, mentor or support students and junior team members as appropriate, and coordinate effectively with internal and external collaborators.

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 or 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, 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:

• 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 broad audiences.
• Ability to work independently, manage priorities and deadlines, and contribute effectively within an interdisciplinary and 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.

Instructions for Applying:

Link to apply: http://explore.msujobs.msstate.edu/

Applicants should complete the online application at explore.msujobs.msstate.edu and upload:

• A cover letter describing research interests and alignment with the position;
• A current curriculum vitae or résumé.

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, (662) 325-5839.

What do I do if I need an accommodation?

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: (662) 325-3713 or ada@hrm.msstate.edu.

If you have any questions regarding this policy, contact the Department of Human Resources Management at (662) 325-3713 or ada@hrm.msstate.edu. Upon request, sections of this job listing are available in large print, and readers are available to assist the visually impaired.

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