Machine Learning R&D Co-Op

🏢 Emerson
📍 Marshalltown, United StatesFull-timeOn-site
📅 Posted: 1w ago🔄 Updated: 1w ago
CV%
✨ AI Summary
This Machine Learning R&D Co-Op role involves participating in the architecture of data collection, organization, and analysis for AI/ML diagnostics and prognostics R&D. The intern will design and conduct lab experiments, perform exploratory data analysis, and work with R&D and data science teams to improve AI/ML models. Responsibilities include documenting and presenting progress, assisting with project activities, and working in a multi-disciplinary agile team. The role requires enrollment in a Bachelor's degree program in a relevant engineering or science field and experience with technical computing languages like Python, Matlab, or LabView. Strong analytical, problem-solving, documentation, and communication skills are essential.
Required Skills
Information Technology
PythonTechnical Documentation
Other
Matlab
Engineering, Construction & Trades
LabVIEW
Soft Skills & Professional Competencies
Analytical SkillsProblem SolvingCommunication
Nice to have:
Information Technology
NumPyPandasSciPyScikit-learnPyTorchTensorFlowTime-Series DatabasesRegression TestingAnomaly DetectionClusteringData VisualizationTechnical DocumentationDashboardsDatabase Design
Other
sensor datafilteringfeature extractionfrequency-domain analysisclassificationneural networksprobabilistic modelsstorage tools
Science & Research
Statistical Modeling
🎁 Benefits & Perks
medical insurance plans, with dental and vision coverage, flexible time off plans, paid holidays, volunteer time, hands-on experience, professional development, networking opportunities, on-site cafeterias, fitness facilities, employee resource groups.
Requirements
Must be enrolled in a Bachelor's degree program in Mechanical Engineering, Electrical Engineering, Computer Engineering, Computer Science, Data Science, Mathematics, Statistics, or a related engineering/science field. Must have experience with Python, Matlab, LabView or similar technical computing language. Must have the ability to work in a laboratory environment and follow structured experimental procedures. Strong analytical, problem-solving, documentation, and communication skills are required.
Description
In This Role, Your Responsibilities Will Be:
  • Participate in the architecture of data collection, organization, and analysis from various sources including manufacturing and global service partners for AI/ML based diagnostics and prognostics R&D.
  • Design, plan, and conduct lab experiments to generate high-quality data for evaluating, validating, and improving AI/ML models for diagnostics and prognostics research.
  • Work with R&D and data science teams to perform exploration data analysis, identifying trends and features.
  • Help plan & roadmap new features and functionality.
  • Work in a multi-disciplinary agile team supporting research, data science, and prognostics teams in developing and improving AI/ML models.
  • Document and present progress/results to the data science and prognostics teams as well as other stakeholders.
  • Assist with other project activities as assigned.
     
Who You Are:
  • You are self-motivated. You balance planning with actions. You solicit both input and discussion. You focus on priorities and set stretch goals.

 
For This Role, You Will Need:
  • Enrollment in a Bachelor's degree program in Mechanical Engineering, Electrical Engineering, Computer Engineering, Computer Science, Data Science, Mathematics, Statistics, or a related engineering/science field.
  • Experience with Python, Matlab, LabView or similar technical computing language.
  • Ability to work in a laboratory environment and follow structured experimental procedures.
  • Strong analytical, problem-solving, documentation, and communication skills.

 
Preferred Qualifications That Set You Apart:

 

  • Junior or higher class standing
     

  • Cumulative GPA of 2.5 or higher 
     

  • Experience with Python-based data science and machine learning tools such as NumPy, pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar libraries.
     

  • Familiarity with time-series data, sensor data, signal processing, filtering, feature extraction, or frequency-domain analysis.
     

  • Exposure to machine learning methods such as classification, regression, anomaly detection, clustering, neural networks, or probabilistic models.

  • Experience designing or supporting lab experiments, test plans, data acquisition, or Design of Experiments.

  • Interest in diagnostics, prognostics, predictive maintenance, reliability engineering, or condition-based monitoring.

  • Ability to connect experimental observations with physical system behavior and communicate findings clearly to both technical and non-technical audiences.

  • Experience with data visualization, technical reporting, dashboards, or database/storage tools is a plus.
     

Our Culture & Commitment to You:
  • At Emerson, we prioritize a workplace where every employee is valued, respected, and empowered to grow. We foster an environment that encourages innovation, collaboration, and diverse perspectives—because we know that great ideas come from great teams. Our commitment to ongoing career development and growing an inclusive culture ensures you have the support to thrive. Whether through mentorship, training, or leadership opportunities, we invest in your success so you can make a lasting impact. We believe diverse teams, working together are key to driving growth and delivering business results.
  • We recognize the importance of employee wellbeing and know that to do your best you must have flexible, competitive benefit plans to meet your physical, mental, financial, and social needs. We provide a variety of medical insurance plans, with dental and vision coverage. Our culture prioritizes work-life balance and offers flexible time off plans, including paid holidays and volunteer time. You will also get hands-on experience, professional development, and networking opportunities in our well-established and structured co-op program. There is also an easy to access on-site cafeterias, fitness facilities, employee resource groups, recognition, and much more.

 

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🎯 Overalli74%
⚡ Skillsi85%
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Ontology Match: 85.0
Matched:✓ Requirements Matching✓ Ontology Skills Mapping
📜 Eligibilityi49%
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Local: 19600%
🏗️ Career Fiti91%
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Seniority: 91.0
📋 Requirementsi67%
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Domain: 67.0
🔥 Motivationi78%
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Title Fit: 78.00