Postdoc Fellow - Chemical and Environmental Engineering

1w1 week ago

University of Cincinnati

Cincinnati, US · Full-time · $55,000 – $65,000

About this role

The Terrestrial Hydrology Lab in the Department of Chemical and Environmental Engineering invites applications for a post-doctoral researcher. This role supports a NASA-funded project developing an advanced early warning system for river water quality management. Research targets hindcast and forecast of riverine turbidity and harmful algal blooms.

Leveraging satellite observations and machine learning, the project bridges Earth observation data with actionable water quality management. Collaborating with end-user partners ensures user-centered data and tools for improved decision-making. The focus integrates multi-source observations systematically.

UC thrives on innovation as a Carnegie 1 institution and anchor of the Cincinnati Innovation District. Staff and faculty contribute to student success and community transformation through scholarship. The oldest co-op program provides paid experiences generating significant economic impact.

Initial appointment lasts one year with potential renewal for two more years based on performance and funding. Flexible start between June 2026 and August 2026 allows alignment with candidate availability. Lead publications and conference presentations advance career in the field.

Requirements

Ph.D. in Hydrology, Geosciences, Environmental Engineering, Water Resources, Computer Science, Statistics, or related field (conferred by start date)
In-depth knowledge of specialized field, process or discipline
Experience with specialized software programs
Strong background in satellite remote sensing and surface water quality processes
Experience in machine learning/deep learning and surface water quality modeling
Experience in high-performance computing
Demonstrated written and verbal communication skills with track record of leading high-quality scientific publications
Experience in data visualization and development of decision-support tools

Responsibilities

Develop and implement machine learning/deep learning models to integrate multi-source Earth observations for predicting river turbidity and HABs
Work closely with science team and end-user partners to develop user-centered tools and implementation protocols that improve water quality decision-making
Lead peer-reviewed publications on research findings
Present research findings at major conferences
Analyze satellite remote sensing data for surface water quality parameters
Validate model predictions using in-situ observations and historical data
Utilize high-performance computing for model training and simulations

Benefits

Initial one-year appointment with potential renewal for two additional years contingent upon performance and funding
Flexible start date between June 2026 and August 2026