COLLEGE CO-OP WASTEWATER ENGINEERING (GIS/Acoustic Sound/LiDar)

City of Cincinnati; Cincinnati (OH); On-site; USD 25,000 - 30,000; Part time

Job summary

The City of Cincinnati, through the Metropolitan Sewer District, offers college co-op opportunities for Spring 2027. Interns will work in a professional engineering environment, focusing on GIS, LiDAR data, and Python-driven data analysis.

The program emphasizes data collection, analysis, and the development of tools to improve efficiency and reduce costs. Ideal candidates are current college students in CS or engineering, with strong Python abilities, Linux familiarity, and a GPA of 3.4 or

Qualifications

• College student currently enrolled in CS or engineering coursework.
• Ability to author/work with Python code and analyze large data sets.
• GPA 3.4 or higher; Calculus I with A- or better; familiarity with Linux.
• Familiarity with Fourier transforms and wave concepts helpful.

Responsibilities

• Work on acoustic sensing hardware selection and data collection.
• Refine LiDAR data collection and create 3D point clouds for MSD infrastructure.
• Apply AI techniques to analyze datasets and automate data archiving.
• Use ArcGIS to log data and perform regional analysis.

Skills

Python programming

Data analysis

GIS / ArcGIS concepts

LiDAR data processing

Education

CollegeCS/Engineering coursework

GPA 3.4 or higher

Calculus I (A- or better)

Tools

ArcGIS

LiDAR

Python

Linux OS

Job description

The Metropolitan Sewer District posted a number of College Co-Op Job Postings for the Spring Semester beginning January 18, 2027. Please read through all Job Postings and apply for the position(s) you would like to be evaluated for and/or interviewed for as a Co-Op Student Intern. Each job Project Plan is included in the Job Postings. For more information about the different projects please contact [e-mail].

The Priority Deadline for applications is November 8, 2027. Applications submitted by this date will be reviewed by MSD hiring managers before the posting closes on November 20, 2027. If selected for an interview, students will be notified via email as early as the week of November 15, 2027. All applications are accepted through the posting close date.

All applicants should have availability for work scheduled 32 - 40 hours per week.

MSD WASTEWATER ENGINEERING GIS and LiDar

Mission:

Learn the value of data collection and its applicability to industrial uses, as well as the limitations and challenges of budget and time constraints. Tackle through a hands-on experience, the philosophical question of how to balance the cost to obtain information and its quality vs. the value it provides.

Purpose:

Develop tools to improve response time and reduce costs for data collection related to .infrastructure. Apply applications to sensors and micro-computers which can be used in the field to take measurements. If time permits, work on ArcMap GIS applications and develop Python routines to automate desired, repetitive tasks performed by MSD users.

Overview:

Work as part of a team in a professional engineering environment. Develop communication skills both with engineers as well as maintenance staff. Learn about sewer infrastructure and the factors that affect its performance. Learn about data collection and analysis and its applicability to civil engineering and sewer design. Assume responsibility for ethical action and work production.

Expectations:

1. Work on developing an acoustic system for detecting stormwater pipe connection to MSDGC’s sewers. This work may include researching and recommending hardware, using hardware, coding, data collection, analysis, and field work.
2. Work on refining LiDAR data collection and analysis to create 3D point clouds, and modifiable renderings with measurable dimensions of MSD infrastructure or environments affecting MSD sewer performance. The work may require changing or refining existing software applications already developed by MSD. Working with microcomputers, controllers, and sensors, as well as some basic fabrication is expected. 3D printing and related modeling are also anticipated. Finally, field work and testing of devices is likely.
3. Work on the application of artificial intelligence (AI) to analyze collected data from acoustic testing, LiDAR, flow meters, or other datasets. This work may also involve developing an AI tool to assist with archiving paper records and automating the transfer of data into searchable databases.
4. Use ArcGIS to log data and perform regional analysis.

Co-op Learning Deliverables:

• -Advances in effective acoustic testing methods for MSD.
• -Advances in MSD’s LiDAR data collection.
• -Advances in the use of AI for MSD’s data analysis and archiving of paper records.
• -Updates to GIS mapping of MSD infrastructure.

MSD to provide:

• -Budget: desktop or laptop computer, micro-computers, controllers, LiDAR units, movement tracking sensors, acoustic equipment, safety gear for field work, AI development tools, co-op compensation.
• -Logistics: workstation is in MSD’s WEEC (engineering) Building.
• -Training: training on city policies, rules, regulations.

Milestones

Orientation (week #1)

Needs Assessment (week #2)

Begin Project Work (weeks #1 - 3)

Project Manager and co-op will work together to defines projects and timelines that ensures that project goals and objectives will be achieved. The projects will be tailored to suit the student’s interests and abilities.

Continuation of Project Work(weeks #4 - 14)

Investigate solutions, gather information from various sources, and work as necessary to complete project deliverables as well as possible additional ideas on project solutions.

Perform mid-term review of project schedule and timeline at week #8. Make necessary adjustments to meet project objectives and project manager’s expectations.

Prepare Final Documentation and Report Out (weeks #15 - 16)

Conclude projects, where possible.

Provide documentation and discuss with necessary parties to enable continuation of unfinished work.

Summarize and evaluate lessons learned.

Education Requirements:

The applicant must currently be a college student at the time of applying, with successful completion of college classes in computer science or engineering. Ideal candidates will possess the ability to author or work with Python code and analyze large volumes of data, applying math and science. Below, a more detailed list of desired skillsets is provided.

Required:

• Familiarity with Fourier transforms.
• Familiarity with wave functions.
• An understanding of wave propagation, and the differences between light vs. sound waves.
• Collect, process, and export large datasets and using trigonometric functions.
• Completion, as a minimum, Calculus I with an overall grade of “A-”, or better (or equivalent).
• A collegiate math and science cumulative GPA of 3.4, (on a 4.0, unweighted scale), or better.
• Familiarity with Linux as well as Microsoft operating systems, environments, and parameters.
• Familiarity with computer blogs, or other computer science community resources.
• Resourcefulness in finding solutions when sensors fail to communicate or work as intended.

Desired, but not required:

• Ability to utilize artificial intelligence and algorithms for use with analyzing video imagery.
• Familiarity with electronics and power requirements including resistance, voltage, and amperage.
• Experience tutoring or teaching.
• Familiarity with 3D printing.
• Familiarity with Esri ArcMap.
• Ability to code in Python.
• Familiarity with the application of AI and developing application tools with AI.
• Ability to set up environments on micro-computers and install peripheral devices for sensing and data collection which can communicate with the micro-computer and the code written by the applicant.
• Ability to set up Linux operating systems on micro-computers, then install and run Python code.
• Ability to import and export large datasets across a micro-computer vs. more powerful computing platform (desktop or laptop computer).

Use of Python and math to create intuitive, easily discernible, yet accurate and informative visual representation of coordinate (x,y,z) data clouds.

In order to qualify for the Intern/Co-op Program, a student must:

• Be a U.S. citizen, lawful permanent resident, or a non-citizen with proof of eligibility to work in the United States
• Individuals under eighteen will require a work permit
• Submit a City job application for employment
• Must pass a drug screen and background check