Part Time Water Sample Collection Jobs in Rochester, NY

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Job Location (Full Address):

220 Hutchison Rd, Rochester, New York, United States of America, 14620

Opening:

Worker Subtype:

Regular

Time Type:

Part time

Scheduled Weekly Hours:

25

Department:

400038 Dermatology M&D

Work Shift:

UR - Day (United States of America)

Range:

UR URG 104 H

Compensation Range:

$19.04 - $26.63

Responsibilities:

This position supports the collection, processing, and analysis of Lake Ontario water samples to identify and enumerate microplastic particles. Water samples are collected monthly from the east and west sides of the Charlotte Beach pier using plastic-free collection containers and reagents, followed by filtration using nanomembrane technology. The role learns, applies, and improves Nile red staining and imaging protocols and collaborates with colleagues at RIT and the University of Rochester air-sampling group to develop AI-driven methods for particle enumeration. The position communicates results through weekly laboratory and one-on-one meetings with the PI and contributes to Lake Ontario Center for Microplastic and Human Health (LOMP) All-Hands, Particles Protocol, and Journal Club meetings.

ESSENTIAL FUNCTIONS

• Prepare for and conduct monthly Lake Ontario water-sampling activities at the Charlotte Beach pier, collecting samples from both the east and west sides in accordance with established sampling plans and contamination-control procedures. Generate and maintain plastic-free collection containers and reagents; clean glassware and related materials; label, transport, and document samples accurately; and maintain complete collection records and chain-of-custody information as applicable.
• Process and analyze water samples to identify and enumerate microplastic particles. Perform nanomembrane filtration, prepare and stain samples using the Nile red protocol, capture and evaluate images, and use ImageJ or other approved image-analysis tools to quantify particles. Calculate, verify, record, and organize results; maintain accurate laboratory records; apply quality-control measures; identify possible contamination or anomalous findings; and repeat or troubleshoot analyses when results do not meet established criteria.
• Contribute to collaborative research aimed at improving microplastic detection and analysis. Evaluate and refine the Nile red staining and imaging protocol, document proposed procedural changes, compare results across methods, and assist with validation of revised protocols. Collaborate with colleagues at RIT and the University of Rochester air-sampling group to develop, train, test, and improve AI-driven algorithms for particle recognition and enumeration, including preparing annotated datasets, reviewing algorithm outputs, and communicating findings and limitations to the project team.
• Maintain a clean, organized, and contamination-controlled laboratory work area. Clean laboratory equipment and perform routine preventive maintenance and operational checks on filtration, staining, imaging, and related equipment; maintain maintenance and usage records; monitor supplies and reagents; and promptly report equipment malfunctions, safety concerns, or supply needs to the PI or appropriate laboratory personnel.
• Communicate research progress and contribute to the scientific work of the laboratory and LOMP. Participate in weekly laboratory meetings by providing organized data and project updates, discussing methods and results, responding to feedback, and periodically leading journal club. Participate in weekly one-on-one meetings with the PI to review priorities, troubleshoot barriers, and establish next steps. Attend and actively contribute to monthly LOMP All-Hands, Particles Protocol, and Journal Club meetings, including sharing relevant findings, reviewing scientific literature, and coordinating activities with internal and external collaborators.

MINIMUM EDUCATION & EXPERIENCE

• High School diploma or equivalent and 5 years of relevant experience required
• Associate's degree preferred
• Bachelor's degree strongly preferred
• Or equivalent combination of education and experience

KNOWLEDGE, SKILLS AND ABILITIES

• Computational expertise, ability to work independently and problem solve. Willingness to learn new things. Develop protocols; preferred.

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