workday
Posted 22 weeks ago
Postdoctoral Researcher
Job description
The Postdoctoral Researcher will serve as a numerical modeler and programmer within the coastal systems modeling group led by Dr. Y. Joseph Zhang at CCRM. This position supports ongoing and emerging research initiatives focused on coastal hydrodynamics, water quality, and environmental forecasting using physics-based and AI-driven modeling approaches. The incumbent will contribute to the development of next-generation, seamless “creek-to-ocean” operational modeling systems based on the SCHISM framework, collaborate with interdisciplinary research teams, engage with graduate students and visiting scientists, and pursue independent research aligned with CCRM and VIMS strategic priorities. Required
Qualifications
Education
Earned Ph.D. in a relevant field such as computational science, applied mathematics, or physical oceanography. Competencies: Demonstrated strong quantitative, numerical modeling, and programming skills, including web-based programming. Broad knowledge of coastal and estuarine systems.
Experience
Experience
applying numerical models to oceanic and estuarine systems. Record of peer-reviewed research and scholarly publication appropriate to career stage.
Preferred Qualifications
Education
Record of peer-reviewed research and scholarly publication appropriate to career stage. Competencies: Expertise in uncertainty quantification and statistical methods.
Experience
with data assimilation techniques.
Experience
applying machine learning approaches to ocean or coastal modeling.
Experience
Hands-on experience with unstructured grid numerical models, particularly SCHISM. Demonstrated experience working in interdisciplinary research teams. Salary - up to $70,000.00 commensurate with experience Conditions of employment: This is a term restricted position, subject to the continued availability of funding. Core
Duties
and
Responsibilities
Research and Project Support (75%) Conduct advanced numerical modeling research in support of the Center of Excellence for Environmental Forecasting (CEEF), with a primary focus on recurrent flooding, coastal resilience, and related coastal system processes. Apply physics-based and AI-based modeling approaches to simulate coastal hydrodynamics, water quality, sediment transport, and estuarine processes using established and emerging modeling frameworks, including SCHISM. Contribute to the development, testing, calibration, and implementation of next-generation “creek-to-ocean” operational modeling systems. Support other funded research projects aligned with CEEF priorities, including projects related to flooding dynamics, sediment transport, and coastal and estuarine systems modeling. Work closely with faculty investigators, research collaborators, graduate students, and visiting scientists to support ongoing research activities and project deliverables. Assist with model setup, data processing, analysis, visualization, and interpretation of results to support project objectives and decision-making needs. Scholarly Publications (15%) Prepare high-quality manuscripts for submission to peer-reviewed scientific journals based on modeling results and research findings. Collaborate with project team members and co-authors to synthesize results and develop clear, well-documented scientific publications. Respond to reviewer feedback and revise manuscripts as needed to support successful publication. Maintain an active research and publication record consistent with the expectations of externally funded research projects. Proposal and Report Development (10%) Assist in preparing technical reports and research summaries for project sponsors, funding agencies, and other stakeholders. Contribute modeling results, figures, methods descriptions, and technical narratives for project reports and deliverables. Support the development of grant proposals by assisting with technical content, modeling approaches, and research methodology sections. Participate in proposal development efforts to help secure continued and new external research funding aligned with CCRM and CEEF priorities. Additional Job Description: Job Profile: JP0518 - Postdoctoral Research Associate (12 months) - Exempt - Salary - S99
Qualifications
Compensation Grade: S99 Recruiting Start Date: 2026-02-12 Review Date: Position Restrictions: EEO is the Law. Applicants can learn more about William & Mary’s status as an equal opportunity employer by viewing the "Know Your Rights" poster published by the U.S. Equal Employment Opportunity Commission. https://www.eeoc.gov/know-your-rights-workplace-discrimination-illegal Background Check: William & Mary is committed to providing a safe campus community. W&M conducts background investigations for applicants being considered for employment. Background investigations include reference checks, a criminal history record check, and when appropriate, a financial (credit) report or driving history check. Remote Work Disclaimer: Remote work eligibility is not guaranteed and is subject to approval. Employee eligibility depends on the likelihood of the employee succeeding in a remote work arrangement and the supervisor’s ability to manage remote workers. Departments and/or Human Resources may amend, alter, change, delete, or modify eligibility. William & Mary and the Virginia Institute of Marine Science (VIMS) are vibrant, innovative and engaged communities and we are delighted about your interest in a career with us. Please be aware Workday has weekly downtimes and will be unavailable Fridays starting at 9:00 p.m. through Saturdays at noon (ET) for scheduled maintenance. During this time, the portal will be closed and will not accept applications. William & Mary offers a competitive range of benefits that support employee well‑being and professional growth, including access to on‑campus fitness facilities, university libraries, and other wellness resources. Educational assistance, professional development opportunities, and a robust holiday schedule are also available. Learn more and explore our comprehensive benefits website.
Skills and functions
- Human Resources
- Machine Learning