Machine Learning Co-op: Earth Observation & Climate Data Science

Woods Hole Oceanographic Institution

Posted 3 months ago

Internship

Mount Vista, Washington

In Person

Smart Summary

Responsibilities

The co-op will develop machine learning models and scalable data pipelines to analyze Earth observation data from satellites and autonomous vehicles. They will also create interactive visualization tools to extract insights from large, multi-scale observational datasets.

Qualifications

You are pursuing a degree in a quantitative field like Data Science or Computer Science and have strong Python programming skills, including Git. You possess working knowledge of statistics, time series analysis, and machine learning models (gradient boosting, deep learning) with experience in PyTorch or TensorFlow and geospatial tooling.

Must Have Skills for ATS

Python

Git

statistics

time series analysis

gradient boosting

deep learning

PyTorch

TensorFlow

geospatial

HDF5

NetCDF

Job Description

Job Summary

Machine Learning Co-op: Earth Observation & Climate Data Science

The Woods Hole Oceanographic Institution is seeking one co-op student to contribute to research and climate information products that integrate Earth observations from satellite, autonomous surface vehicles, and in situ platforms. The co-op will work with research scientists on active projects developing machine learning models, building scalable data pipelines, and creating interactive visualization tools to extract insight from large, heterogeneous, multi-scale observational datasets.

Job Description

Required Qualifications

  • Pursuing a degree in Applied Mathematics, Data Science, Computer Science, Marine and Environmental Sciences, or a related field
  • Strong proficiency in Python, including experience with version control (Git) and writing modular, well-documented, maintainable code
  • Working knowledge of statistics, time series analysis, and linear and non-linear modeling
  • Hands-on experience with machine learning for Earth observation, including gradient boosting and deep learning methods using PyTorch or TensorFlow; experience with advanced architectures such as graph neural networks (GNNs) or physics-informed neural networks (PINNs) is a strong plus
  • Experience with geospatial and scientific Python tooling for handling multi-dimensional Earth observation data

Preferred Qualifications

  • Experience managing large datasets and producing technical data reports
  • Familiarity with oceanographic and geophysical data formats such as HDF5 or NetCDF
  • Strong communication, problem-solving, and organizational skills
  • Strong work ethic, with the ability to work independently and take initiative on technical projects

Additional Job Requirements

Fixed Hourly Rate:

• $27.50/hour – 1st Co-op, Engineering Assistant I
• $29.00/hour – 2nd Co-op, Engineering Assistant II
• $31.00/hour – 3rd Co-op, Engineering Assistant III

The hourly rate provided for this position reflects the set base pay for new hires. Final level placement will be determined based on factors such as relevant skills, experience, and qualifications, as well as internal equity and market conditions. These appointments are casual status, temporary positions and eligible for casual benefits.


Position Details

  • Dates: July – December 2026
  • Schedule: Full-time
  • Application deadline: June 26, 2026

Eligibility

  • Junior, senior, or graduate student with at least one semester of school remaining at the time of the co-op assignment
  • Minimum GPA of 3.0
  • Available to work full-time for the duration of the co-op

WHOI accepts applications on a rolling basis - applications will be reviewed as they are received, and we encourage you to submit your application as soon as possible to ensure full consideration. While we will continue to review applications until the position is filled, and early applicants may have an advantage in the selection process.

EEO Statement

Woods Hole Oceanographic Institution (WHOI) provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. 

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Woods Hole Oceanographic Institution

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