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Statistics Research Intern Jobs in Colorado (NOW HIRING)

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Currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field, and returning to that program after the co-op.

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Currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field, and returning to that program after the co-op.

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Currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field, and returning to that program after the co-op.

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Currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field, and returning to that program after the co-op.

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Currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field, and returning to that program after the co-op.

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Statistics Research Intern information

What does a statistics research intern do?

A Statistics Research Intern assists in analyzing and interpreting data, designing experiments, and applying statistical methods to solve real-world problems. They work under the supervision of experienced statisticians or researchers and may contribute to data cleaning, visualization, and the preparation of reports or presentations. Interns often use statistical software such as R, Python, or SAS to carry out their tasks and may also review relevant literature to support ongoing research projects.

What are the key skills and qualifications needed to thrive as a statistics research intern?

To thrive as a Statistics Research Intern, you generally need a solid grounding in statistical theory, data analysis, and a relevant field of study such as mathematics, statistics, or data science. Familiarity with statistical software such as R, Python, SAS, or SPSS is typically required, and coursework or certifications in these tools is advantageous. Strong analytical thinking, attention to detail, and effective communication skills help interns interpret results and convey findings clearly. These competencies are crucial for producing accurate, insightful research that supports evidence-based decision-making.

What are the most commonly searched types of Statistics Research jobs in Colorado?

The most popular types of Statistics Research jobs in Colorado are:

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For Statistics Research Intern jobs in Colorado, the most frequently searched job titles are:

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Statistics Research Intern jobs near you

2027 Internship Opportunity: Research & Innovation Support Intern

Association of American Railroads

Pueblo, CO • On-site

Full-time

Posted 5 days ago

Job description

Overview:

The internship will support the Association of American Railroads (AAR) Strategic Research Initiative (SRI) inspection program, particularly rail and wheel inspection projects.

Projects:

  • Rail Inspection
    • Machine learning on raw time-series ultrasonic data (A-scans)
    • Integrate an edge computing device with ultrasonic hardware/software for real-time A-scan analysis and processing
    • Develop time-series ultrasonic and electromagnetic data fusion approach for rolling contact fatigue (RCF) characterization in rails
    • Demonstration of developed approach/methodology
  • Wheel Inspection
    • Wheel sub-surface fatigue crack (SSFC) growth monitoring using a multi-sensor data fusion approach
    • Develop data fusion methodology
    • Demonstrate the developed approach/ methodology

Preferred Level of Education:

  • M.S. or Ph.D. students in the Engineering field or computer Science/ Data Science.

Primary Responsibilities:

  • Data Preprocessing: Clean, normalize, and annotate large inspection datasets (e.g., images, time-series signals).
  • Data Fusion Implementation: Develop algorithms (e.g., Kalman filters, deep learning architectures) that merge data from multiple inspection sensors to improve defect detection accuracy.
  • Model Training: Build and train machine learning models (CNNs, RNNs, or Transformers) using frameworks like PyTorch or TensorFlow to classify flaws or predict material fatigue.
  • Edge Optimization: Deploy, quantize, and compress trained AI/ML models to run efficiently on low-power, localized edge devices (e.g., embedded systems, IoT sensors).
  • Testing & Validation: Validate model outputs using statistical bounds and Probability of Detection (POD) studies.
  • Ensure that all duties and responsibilities are performed in a safe manner.
  • Perform other related duties as assigned.

Apply