The Olivares' Lab, part of the Civil and Environmental Engineering (CEE) Department at the University of California, Irvine (UCI), is currently seeking two ambitious MS/Senior Undergraduate students to assist in the following projects:

Data & Computer Science Relevant Projects: (Computer-based)

• Analysis and Machine Learning Prediction of the PFAS Contamination in U.S.
• Global Change Impacts on Groundwater Contaminants.

In computer-based projects, they will develop database and machine learning algorithms for the state-of-the-art environment, climate change, and sustainability models. This unique opportunity will allow you to bridge the gap between computer science and environmental science while contributing to groundbreaking research to publish in top-tier conferences and journals across both fields.

* Required Skills:

• Familiar with Python-based machine learning frameworks and coding
• Experience in managing big data sets

Environmental Chemistry & Sensing Relevant Projects: (Lab-based)

• PFAS FAST Detection.
• Possible PFAS direct pathway in human

In lab-based projects, they will use LCMS to measure PFAS in the water and from various sources and try different sensing techniques to detect PFAS. This unique opportunity will allow you to learn to use high-end instruments while contributing to groundbreaking research to publish in top-tier conferences and journals.

* Required Skills:

• Laboratory experience
• Sensing equipment experience

* What you will obtain:

• Opportunity to publish papers in recognized conferences/journals.
• Close collaboration with esteemed Senior Ph.D. Jialin Dong and Professor Christopher Olivares (https://olivareslab.org/).
• A reference letter reflecting your performance and contributions to the project.
• Earn corresponding academic credits.
• Detailed insights into Jialin Dong's current projects can be accessed here: https://sites.google.com/uci.edu/jialin-dong/current-projects

To express interest in these positions, please contact Jialin at jialind2@uci.edu. Be sure to attach your CV and specify the approximate number of hours you can dedicate to the project each week in your application. More details can be found in the poster.