Water Quality Postdoc Jobs (NOW HIRING)

Posting Details
Posting Details
Job #
078788
Job Title
Postdoctoral Scholar - AI in Earth and Environmental Sciences
Location
Syracuse, NY
Campus
Syracuse, NY
Commitment to On-Campus Experience
Syracuse University is committed to delivering an exceptional student experience through vibrant, engaged campus communities. This position is based at the above campus location and requires regular in-person presence to support our students, collaborate with colleagues, and contribute to our thriving academic environment. Syracuse University values the collaboration, mentorship, and spontaneous connections that happen when our community works together on campus. Remote work arrangements are limited in accordance with University policy.
Pay Range
$62,400 - $70,000
Pay Determination
Salary offers at Syracuse University will be based on education, experience, and relevant skills, as well as the academic or professional discipline of the position in the context of the home department, school, or college. Salary offers may also be influenced by prior relevant work or industry experience, where applicable. Faculty pay ranges are for 8.5 months' salary unless otherwise specified.
FLSA Status
Exempt
Hours
Determined by supervisor.
Job Type
Full-time
Rank
Post Doc
Unionized Position Code
UA
Job Description
The Department of Earth and Environmental Sciences at Syracuse University invites applications for a Postdoctoral Scholar position in the Hydrogeochemistry and Environmental Data Sciences (HANDS) research group. The position is broadly focused on artificial intelligence, machine learning, environmental data science, foundation AI models, and data-intensive Earth and environmental research.
The successful candidate will contribute to two complementary research directions. One direction uses AI/ML, data science, and geologic/environmental datasets to assess energy and environmental systems, including oil and gas well condition, characterization, and integrity-related questions. The second direction focuses on characterizing global water and elemental cycles, with emphasis on terrestrial and catchment systems. Together, these projects will use large geochemical, hydrologic, geospatial, regulatory, and environmental datasets to advance predictive, interpretable, and transferable approaches for Earth and environmental sciences.
A key intellectual theme of the position is the development and application of AI/ML and foundation-model approaches for complex Earth and environmental systems, including subsurface energy infrastructure, riverine hydrogeochemistry, watershed elemental cycles, water quality, terrestrial water and solute fluxes, and prediction across watershed and river-network scales.
This position is part of a bargaining unit and is represented by the union SEIU, Local 200United.
Qualifications

• Ph.D. in geoscience, hydrology, geochemistry, environmental science, civil/environmental engineering, data science, computational geoscience, Earth system science, or a closely related field by the anticipated start date.
• Demonstrated experience in artificial intelligence, machine learning, environmental data science, statistical modeling, or related quantitative methods.
• Strong quantitative, programming, and data analysis skills.
• Ability to work with complex environmental, geospatial, hydrologic, geochemical, or Earth system datasets.
• Ability to develop reproducible computational workflows.
• Evidence of scientific communication through publications, presentations, reports, software, datasets, or related scholarly products.
• Ability to work both independently and collaboratively in an interdisciplinary research environment.

Job Specific Qualifications
Preferred qualifications include experience or interest in one or more of the following:

• AI/ML, statistical modeling, or data science applications in energy and environmental systems.
• Oil and gas well datasets, well characterization, well integrity assessment, subsurface energy systems, environmental risk assessment, or related geologic/environmental infrastructure questions.
• Foundation AI models, representation learning, transfer learning, self-supervised learning, deep learning, interpretable machine learning, uncertainty quantification, data assimilation, or related AI/ML approaches for scientific datasets.
• Application of AI/ML or foundation-model approaches to catchment sciences, hydrology, hydrogeochemistry, water quality, watershed elemental cycles, river networks, or Earth system prediction.
• Experience working with large environmental, geochemical, hydrologic, geospatial, regulatory, remote sensing, or Earth system datasets.
• Experience integrating diverse datasets such as stream chemistry, discharge, hydroclimatic forcings, land cover, lithology, soils, well records, regulatory data, remote sensing products, geospatial attributes, monitoring data, or modeled Earth system outputs.
• Experience developing predictive, interpretable, and transferable models for environmental, geologic, energy, or Earth system applications.
• Experience with scientific programming in Python, R, or similar languages.
• Experience using reproducible research tools such as Git/GitHub, Jupyter notebooks, R Markdown/Quarto, workflow managers, open-science repositories, cloud computing, or high-performance computing resources.
• Research experience or strong interest in hydrology, geochemistry, terrestrial water and elemental cycles, energy/environmental systems, catchment sciences, or Earth system science.
• Experience mentoring students or collaborating in interdisciplinary research teams.
• Strong written and oral communication skills.

Responsibilities
The postdoctoral scholar will be expected to:

• Develop and apply artificial intelligence, machine learning, statistical modeling, foundation-model, and environmental data science approaches to large geochemical, hydrologic, geospatial, regulatory, and related Earth system datasets.
• Develop AI/ML-enabled workflows to characterize energy and environmental systems, including oil and gas well condition and integrity-related questions, using geologic, environmental, and publicly available or regulatory datasets.
• Investigate the potential application of foundation AI models in catchment sciences, including riverine hydrogeochemistry, watershed elemental cycles, water quality, terrestrial water and solute fluxes, and environmental prediction across catchment, watershed, and river-network scales.
• Integrate, clean, manage, and analyze heterogeneous observational, geospatial, remote sensing, modeled, regulatory, and environmental datasets from multiple sources to support interdisciplinary research on energy systems, hydrologic processes, geochemical dynamics, and terrestrial elemental cycles.
• Build reproducible computational workflows for data synthesis, model development, feature engineering, representation learning, transfer learning, uncertainty assessment, visualization, and scientific interpretation.
• Evaluate and interpret model outputs in the context of hydrologic, geochemical, geologic, engineering, climatic, land-use, and anthropogenic controls on energy and environmental systems.
• Contribute to interdisciplinary research design, technical reporting, project coordination, and communication with collaborators and project partners.
• Prepare manuscripts for peer-reviewed publication and contribute to conference abstracts, presentations, reports, and other scholarly products.
• Mentor and support graduate and undergraduate students in the research group, especially in coding workflows, data analysis, reproducible research practices, and scientific communication.
• Participate in regular research group meetings and contribute to a collaborative, interdisciplinary, and supportive research environment.

Physical Requirements
Not Applicable
Tools/Equipment
Not Applicable
Application Instructions
Applicants should submit the following:
• Curriculum vitae
• Cover letter describing research interests, relevant experience, and fit for the position
• Contact information for 3 professional references
• One representative publication, writing sample, software repository, or data-analysis product
About Syracuse University
Syracuse University is a private, international research university with distinctive academics, diversely unique offerings, and an undeniable spirit. Located in the geographic heart of New York State, with a global footprint, and over 150 years of history, Syracuse University offers a quintessential college experience.
The scope of Syracuse University is a testament to its strengths: a pioneering history dating back to 1870; a choice of more than 200 majors, 100 minors, and 200 advanced degree programs offered across the University's 13 schools and colleges; over 15,000 undergraduates and over 6,000 graduate students; more than a quarter of a million alumni in 160 countries; and a student population from all 50 U.S. states and 123 countries. For more information, please visit http://www.syracuse.edu.
About the Syracuse area
Syracuse is a medium-sized city situated in the geographic center of New York State approximately 250 miles northwest of New York City. The metro-area population totals approximately 500,000. The area offers a low cost of living and provides many social, cultural, and recreational options, including parks, museums, festivals, professional regional theater, and premier shopping venues. Syracuse and Central New York present a wide range of seasonal recreation and attractions ranging from water skiing and snow skiing, hiking in the Adirondacks, touring the historic sites, visiting wineries along the Finger Lakes, and biking on trails along the Erie Canal.
EEO Statement
Syracuse University is an equal-opportunity institution. The University prohibits discrimination and harassment based on race, color, creed, religion, sex, gender, national origin, citizenship, ethnicity, marital status, age, disability, sexual orientation, gender identity and gender expression, veteran status, or any other status protected by applicable law to the extent prohibited by law. This nondiscrimination policy covers admissions, employment, and access to and treatment in University programs, services, and activities.
Commitment to Supporting and Hiring Veterans
Syracuse University has a long history of engaging veterans and the military-connected community through its educational programs, community outreach, and employment programs. After World War II, Syracuse University welcomed more than 10,000 returning veterans to our campus, and those veterans literally transformed Syracuse University into the national research institution it is today. The University's contemporary commitment to veterans builds on this historical legacy, and extends to both class-leading initiatives focused on making an SU degree accessible and affordable to the post-9/11 generation of veterans, and also programs designed to position Syracuse University as the employer of choice for military veterans, members of the Guard and Reserve, and military family members.
Commitment to a Respectful and Welcoming Community
Syracuse University fosters a welcoming learning environment where students, faculty, administrators, staff, curriculum, social activities, governance, and all aspects of campus life reflect a broad range of perspectives and experiences. The University community values the many similarities and differences among individuals and groups. At Syracuse, we are committed to preparing students to engage with and appreciate the richness of backgrounds, beliefs, and experiences that shape our society. To achieve this, we strive to cultivate a community that respects and encourages open dialogue, understanding, and mutual respect.
Quick Link
https://www.sujobopps.com/postings/113323
Job Posting Date
06/05/2026
Application Deadline
Open Until Filled
Yes
Priority Consideration
06/22/2026
Job Category
Union/Bargaining Unit
Message to Applicants