Internship Opportunity : Data Science and Research & Innovation Support Intern

Description

Project Name : Data Science / Research & Innovation Support

Interns Preferred Degree : Currently pursuing a master's or Ph.D. in engineering, computer science, or other relevant degrees.

Project Description :

The projects' general objectives include supporting research by way of data collection to improve railway safety, performance, and efficiency. Projects supported may include, but are not limited to, Exploratory Data Analysis (EDA), Supervised Machine Learning (ML) Applications, Feature Importance, Rail Inspection, and Wheel & Axle Inspection Technology. These projects may be funded by the Association of American Railroads as part of MxV Rail's Strategic Research Initiatives program, through the Federal Railway Administration (FRA), MxV Rail's internal research and development, and / or commercial customers.

Primary Duties :

Conduct data analysis, including, but not limited to :

• Exploratory Data Analysis (EDA).
• Supervised machine learning model development and deployment.
• Feature importance and interpretability analysis.
• Statistical analysis of track, wheel, axle, and mechanical data.
• Track and mechanical data collected at FAST or other sources.
• Model development : Assist in building, training, and fine-tuning machine learning and deep learning models, with a primary focus on time series data (e.g., raw UT waveforms, electromagnetic data, other modalities).
• Data processing : Participate in the collection, cleaning, and preprocessing of large datasets used for training and evaluating AI models.
• Algorithm research : Conduct research on state-of-the-art algorithms and emerging AI technologies to improve the accuracy and efficiency of inspection systems.
• Prototyping and testing : Develop proof-of-concept models and test them against real-world data to evaluate performance. Work with engineers to test and validate deployed models.
• Code generation : Write clean, well-documented code in Python to support data pipelines, model building, and system integration.
• Data Fusion : Explore data fusion approaches for UT and electromagnetic data.
• Collaboration : Work closely with cross-functional teams to integrate AI / ML solutions into research.
• Reporting : Document findings, methodologies, and results, and present progress to technical and non-technical stakeholders.
• Ensures that all duties and responsibilities are performed in a safe manner.
• Perform other related duties as assigned.

Requirements

Minimum Qualifications :

Preferred Qualifications :

Length of Service :

The internship term is the summer of 2026 (preferably May through September). Alternative start and end dates may be accommodated based on the selected candidate's availability. Continuation or extension beyond the agreed term will be evaluated based on the intern's performance and MxV Rail's current project needs, funding, and strategic priorities at that time. Please note that extensions are not automatic and may not always be possible. The internship is a full-time position requiring 100% of the intern's work hours. The schedule follows a fortnight (9 / 80) pattern :

Monday-Thursday : 7 : 00 AM - 4 : 30 PM

Friday : 7 : 00 AM - 3 : 30 PM (every other Friday off)

Project Deliverables :

Assist the Data Science and Research & Innovation Team with a variety of tasks that may include :

Conduct a comprehensive EDA on selected data. Use statistical methods and data visualization techniques to understand the data's structure and variables. Maintain a detailed Jupyter notebook file outlining the EDA process, including code, statistical summaries, and visualization. Develop an interactive dashboard (e.g., using Plotly or another library) that allows non-technical users to filter and visualize the data. Present Power PowerPoint presentation summarizing the project.

Develop a supervised ML prediction model based on selected data and questions. Maintain a detailed Jupyter notebook file for the data processing and model training pipeline, with clear documentation. Present a PowerPoint presentation summarizing the project findings.

Analyze the provided dataset to identify which features are the most influential predictors. Maintain a detailed Jupyter notebook file with a function that can be used to select the most relevant features from similar datasets. Develop a list with the rank of the most important features, supported by visualizations. Present a PowerPoint presentation summarizing the project findings.

Explore AI / ML algorithms for utilizing raw ultrasonic and EM data for flaw detection and characterization. Perform data fusion using multi-modality hybrid sensing data. Develop, train, test, and validate AI / ML models / algorithms.

Working Environment and Level of Physical Activity :

The conditions herein are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform essential job functions.

Benefits Overview :

Hourly Rate : $20