Machine Learning Student Intern

The ML and Imaging team within the Computational Sciences (CS) department at The Jackson Laboratory (JAX) is looking for a motivated summer intern interested in spending 10-12 weeks working on graph neural network (GNN) interpretability. Our group has ongoing efforts to develop deep learning methods for integrating multi-omics and cross-species data to enable translational research. The intern will have the opportunity to work under the supervision of computational scientists on the existing effort toward developing and implementing methods for improving GNN explainability.

About Your JAX Internship Experience

Join peers selected from educational institutions across the country for a summer of professional growth and career exploration. As a JAX Intern, you will receive a dedicated mentor in your department and connect with your fellow interns through JAX-sponsored activities.

The ideal start date for this position is by June 3, 2024.

Key Responsibilities

• Survey the relevant research literature space (deep learning, biomedicine, AD, multi-omics/cross-species data integration, model interpretability, etc.)
• Implement and experiment with GNNs and GNN explanation methods applied to omics data.
• Present findings periodically in group meetings
• Participate in other lab activities (journal clubs/seminars, etc.)

Desired Qualifications

JAX encourages applications from a diverse mix of educational backgrounds and experiences. Preferred qualifications include:

• Must be enrolled in a college or university program
• Junior/Senior undergraduate, or graduate student pursuing a degree in Computer Science, Bioinformatics, or a related field
• Experience with programming in Python
• Familiarity with machine learning and deep learning
• Practical experience with ML modeling
• Some research experience at the intersection of ML and biomedicine is a plus

Submission of a cover letter is required for this application.

The hourly rate is $17.50 - $25.00. Hourly rate will be determined based on qualifications and experience.