Coding-Workflow Development in Analytical Chem/Ecology Lab- PFAS-Focus

We are seeking an undergraduate researcher to join our lab focusing on streamlining data workflows in an analytical chemistry lab setting to support research on the contaminants, PFAS. The project will involve developing scripts in R, streamlining and automating analysis pipelines, and improving shared data management and organization via Google Drive and GitHub.  Data originate from an LC-MS/MS (liquid chromatography with tandem mass spectrometry) instrument and are processed in relation to calibration data before being stored for analysis. Optimization of LC-MS/MS workflow and underlying statistics are an additional component of the project.  This is an excellent opportunity to apply and expand your skills in a real research setting, particularly if you are interested in coding, statistics, computer science, or analytical chemistry instrumentation. 

Undergraduate researchers will work closely with a chemistry graduate student and a biology postdoc as day-to-day mentors, with guidance from Dr. Daniele Miranda and Dr. Gary Lamberti.

Name of research group, project, or lab
Stream and Wetland Ecology Lab; PFAS Ecotoxicology Program
Why join this research group or lab?

The Stream and Wetland Ecology Lab (SWEL) is a collaborative research community focused on understanding the ecology, health, and resilience freshwater ecosystems in a changing world. Our research explores how streams, rivers, wetlands, and lakes respond to and interact with environmental stressors, particularly environmental contaminants.

A current research focus in our lab is PFAS (per- and polyfluoroalkyl substances) which are manmade chemicals found in everyday products and can be harmful to human health and the environment. Many are known to be toxic, bioaccumulative, and persistent (nicknamed “forever chemicals”). Public concern is growing about PFAS as they are linked to certain cancers, reproductive issues, and other health concerns. Aquatic ecosystems are often the terminal sink for these pollutants, making freshwater food webs and those who rely on them particularly at risk. 

Logistics Information:
Project categories
Applied and Computational Mathematics and Statistics
Biological Sciences
Chemistry and Biochemistry
Computer Science & Engineering
Student ranks applicable
First Year
Sophomore
Junior
Senior
Graduate Student
Student qualifications
  • Interest or background in coding, statistics, analytical chemistry, or computer science
  • Basic experience with R or willingness to learn quickly
  • Familiarity with cloud-based collaboration tools (e.g., Google Drive) and version control (GitHub) is a plus
  • Detail-oriented, self-motivated, and able to work independently with guidance
Hours per week
1 credit / 3-6 hours
Compensation
Research for Credit
Number of openings
1
Techniques learned
  • Coding in R
  • Version control and collaborative tools (GitHub, Google Drive)
  • Exposure to analytical chemistry workflows (particularly LC-MS instrumentation)
  • Critical thinking and application of statistics to real datasets
Project start
Fall 2025
Contact Information:
Mentor
azachrit@nd.edu
Post-doctoral Researcher
Name of project director or principal investigator
Dr. Daniele Miranda
Email address of project director or principal investigator
ddealmei@nd.edu
1 sp. | 5 appl.
Hours per week
1 credit / 3-6 hours
Project categories
Biological Sciences (+3)
Applied and Computational Mathematics and StatisticsBiological SciencesChemistry and BiochemistryComputer Science & Engineering