Numerical Methods Jobs in Maryland (NOW HIRING)

Job Description Summary
Organization's Summary Statement:
The Agroecology Lab at the University of Maryland and the Adaptive Crops and Systems Laboratory at the USDA-ARS Beltsville Agricultural Research Center is seeking a creative and motivated Post-Doctoral Associate. The Post-Doctoral Associate will apply and extend existing soil-crop process models to agricultural systems affected by coastal stressors, such as saltwater intrusion and flooding. This position is part of ongoing research to better understand the impacts of saltwater intrusion, soil hydrology, and crop response on the Delmarva (MD, DE, VA) Peninsula and beyond. We encourage candidates from a range of modeling and soil/water science backgrounds to apply. This position is based at the University of Maryland, College Park, MD, with some work to be conducted at USDA-ARS in Beltsville, MD. This position is not available for visa sponsorship.
Duties and Responsibilities: This position is funded through a cooperative agreement between the UMD Department of Plant Science and Landscape Architecture and the USDA-ARS Adaptive Crops and Systems Laboratory. The candidate will adapt and apply an existing Finite Element Model (2DSOIL) for soil and water solute transport to agricultural systems experiencing saltwater intrusion and flooding. The applicant will be expected to:
• Adapt existing soil-crop models to simulate salt and water movement in fields affected by saltwater intrusion and coastal flooding on the Delmarva Peninsula.
• Assist with the development of algorithms to simulate flooding and salinity effects on root growth and plant processes such as photosynthesis.
• Develop or refine algorithms to simulate salinity effects on root growth, water uptake, and plant physiological processes.
• Identify, compile, and use field and literature data for model parameterization, testing, and evaluation.
• Contribute to mulch decomposition and nitrogen cycling model components relevant to cover crop and transitional farming systems.
• Participate in ongoing projects in the ARS and UMD labs and provide numerical modeling support as needed.
• Collaborate with scientists and graduate students who are collecting data on saline and periodically flooded soils, and crop performance under salt stress.
• Support with training of graduate students in model application.
• Prepare peer-reviewed manuscripts and technical reports based on modeling results.
Qualifications:
Ph.D. in Soil Science, Agricultural Engineering, Civil Engineering, or a related environmental science field with a strong emphasis on applied mathematics, numerical methods, and modeling is required. Candidates must have:
• A research background in soil science, hydrology, and/or agronomy.
• Experience with soil process simulation models (e.g., finite element, finite difference, or other process-based crop/soil models).
• Proficiency in at least one scientific programming language (e.g., Python, R, MATLAB, C++, or FORTRAN)
• Experience with salinity, waterlogging, and/or abiotic stress processes in soil-plant-water models.
• Familiarity with coastal or transitional agricultural systems, particularly in the Mid-Atlantic U.S.A.
• Demonstrated publication record in relevant areas.
Physical Demands:
Preferences:
Experience with agriculture and soils is strongly preferred. Specific Abilities/Experience required: Extensive programming and numerical methods experience in C++, FORTRAN and Python is a prerequisite, as is a research background in Soil Science, Hydrology and/or Agronomy. Demonstrated programming experience with soil process simulation models such as finite element and finite difference models, and experience with numerical methods and applied mathematics is strongly preferred. Ability to obtain a USDA security clearance for on-site access to US government resources and systems.
Licenses/ Certifications:
Additional Job Details
Minimum Qualifications:
Ph.D. in Soil Science, Agricultural Engineering, Civil Engineering, or a related environmental science field with a strong emphasis on applied mathematics, numerical methods, and modeling is required. Candidates must have:
• A research background in soil science, hydrology, and/or agronomy.
• Experience with soil process simulation models (e.g., finite element, finite difference, or other process-based crop/soil models).
• Proficiency in at least one scientific programming language (e.g., Python, R, MATLAB, C++, or FORTRAN)
Preferred Qualifications:
Experience with salinity, waterlogging, and/or abiotic stress processes in soil-plant-water models; Familiarity with coastal or transitional agricultural systems, particularly in the Mid-Atlantic U.S.A.; Demonstrated publication record in relevant areas.
Required Application Materials: Cover Letter highlighting relevant experience and research interests, CV, contact information for 3 references
Best Consideration Date: 8/24/2026
Posting Close Date: 9/01/2026
Open Until Filled: YES
Financial Disclosure Required
No
For more information on Financial Disclosure, please visit Maryland's State Ethics Commission website.
Department
AGNR-Plant Science & Landscape Architecture
Worker Sub-Type
Faculty Regular
Salary Range
$55,000- $65,000
Benefits Summary
For more information on Regular Faculty benefits, select this link.
Background Checks
Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify anyone from employment. Before any adverse decision, the finalist will have an opportunity to provide information to the University regarding disclosable background check information. The University reserves the right to rescind the offer of employment or otherwise decline or terminate employment if the information reported by the background check is deemed incompatible with the position, regardless of when the background check is completed.
Employment Eligibility
The successful candidate must complete employment eligibility verification (on Form I-9) by presenting documents that establish identity and work authorization within the timeframe required by federal immigration law, and where applicable, to demonstrate renewed employment authorization. Failure to complete employment eligibility verification or reverification within the timeframe set forth by law may result in suspension or termination of employment.
EEO Statement
The University of Maryland, College Park is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment. Please read the University's Equal Employment Opportunity Statement of Policy.
Title IX Non-Discrimination Notice
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