Prof. Gondy Leroy (Management Information Systems) is hiring one MIS/IS/CS GRA for the ongoing Valley Fever project and one MIS/IS/CS GRA for the ongoing PANDAS project. Below are descriptions of each project.
The positions start in Fall 2026 with possible continuation for the duration of the project. These are 0.25 FTE positions (10 hrs per week) with associated benefits and tuition remission (50%).
Students in a master’s program or undergraduate students continuing for a master’s degree may apply. Students who make intellectual contributions to the projects will be added as co-authors to publications.
The positions are only open to students graduating in May 2027 or later.
How to apply:
- Upload a 1-page CV and state which position you are applying for. You can apply for both.
- Highlight on this page your relevant skills, GPA, expected graduation and program, and relevant courses taken.
- Applications will be accepted until the night of August 16th. Once applications are reviewed, applicants will receive an exercise about the jobs, followed by interviews. These positions will be filled in time to start at the beginning of the Fall semester.
As part of our evaluation process, I would like you to complete a programming exercise that demonstrates your approach to solving real-world research problems. You are welcome to complete either project or both projects.
I will place significant emphasis on your design choices, assumptions, reasoning, and the way you justify your approach, not just the final code.
I will review submissions and invite selected candidates for a follow-up interview to discuss your design decisions and ideas for extending your solution in a real-world setting.
You may use tools such as Visual Studio Code, GitHub Copilot, cloud-based coding assistants, or other development tools as part of your solution.
Submission Requirements
For each project you complete, please submit:
- A link to a GitHub repository containing your Python source code.
- An email containing:
- A brief description of your design choices and assumptions.
Any screenshots, results, or a link to a public folder containing supporting materials.
Use the subject “Deep Target NLP GRA – programming exercise” for your email.
Due: Aug 16 2026
Project Option 1: Autism Video Data Collection
We are interested in obtaining public video data relevant to children with autism for future research.
Design and implement a small program, written in Python, that could help locate and collect suitable public video data.
Please include:
- A brief description of your design choices and assumptions.
- An explanation of how you would verify that the videos are relevant and appropriate for the intended research purpose.
- Screenshots of any results, or read-only access to a public folder containing these materials.
Project Option 2: Valley Fever Patient Grouping
Assume that, for each patient, you have structured data describing symptoms and social determinants of health, such as housing stability, employment, education, social support, and access to care.
Design and implement a small program, written in Python, that can automatically create groups of patients who are similar to each other and distinct from other groups. Clustering algorithms are a natural starting point, but you are free to select and justify alternative methods if you believe they are more appropriate.
Please include:
- A brief description of your design choices and assumptions.
- An explanation of how you would evaluate the quality and usefulness of the resulting patient groupings.
- Screenshots of your program running on example or synthetic data and summarizing the resulting patient groups, or access to a public folder containing these materials.
Valley Fever Project Research Assistant
The project focuses on extracting information from clinical notes using machine learning (BERT, LLM) for patient phenotyping.
Preferred Qualifications:
- Python (Numpy, Pandas, Matplotlib, Tensorflow, NLP packages like Spacy, NLTK)
- Jupyter notebooks
- Traditional ML knowledge (n-fold validation, metrics)
- Deep ML Models (BERT, hyperparameter tuning, HuggingFace).
- HPC on campus, Jetstream
- Containerization
- GPA 3.0 or above
PANDAS Project Research Assistant
This person will be working with videos and will need to be able to work with Claude and Codex. We will be looking at videos and labeling the behaviors in these videos.
Preferred Qualifications:
Claude and Codex
- Traditional ML knowledge (n-fold validation, metrics)
- Deep ML Models (BERT, hyperparameter tuning, HuggingFace)
- Containerization
- GPA 3.0 or above
