Postdoctoral Research Associate

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.

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.

• 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…