About the role#
The JMP Life Sciences division develops advanced solutions for AI, machine learning, genomics, and clinical data science. This internship focuses on building new AI-integrated routines for JMP products. You will work on projects involving modern LLMs, agentic design, context engineering, UI design, PyTorch, and XGBoost.
What you'll do#
- Write Python code to build new AI-integrated routines for JMP software.
- Test, benchmark, and document your work.
- Promote your projects through written reports or video presentations.
What you'll need#
- Current enrollment in a Master’s or PhD program in Computer Science, Biostatistics, Biochemistry, Clinical Statistics, Statistical Genomics, Engineering, or a related life-science-analytic field.
- Graduation date no earlier than December 2027.
- Strong coding and communication skills.
- Leadership abilities and a history of taking initiative.
- Legal authorization to work in the United States without sponsorship.
Location & details#
- Location: Cary, North Carolina.
- Term: Summer 2027 (May 18, 2027 - August 6, 2027).
- Modality: Hybrid.
- Employment type: Full-time, paid internship.
About JMP
JMP develops statistical discovery software for data analysis and visualization. Founded in 1989, the company provides tools for fields like pharmaceuticals, green energy, and high-tech manufacturing. It operates from its headquarters in Cary, North Carolina, with additional offices across the Americas, Europe, and Asia. The company employs between 201 and 500 people.
How to get in at JMP
Applying early gives you a distinct advantage at JMP because recruiters review applications as they arrive. Intern Insider sends an instant alert the moment a role matching your target is published anywhere, so you apply among the first before the pile grows. This helps you avoid the frustration of submitting your materials to a crowded queue. You can also improve your odds by reaching out to the right people. Intern Insider surfaces the recruiters behind the company roles so you can contact them directly to ask about the position or a referral. This approach materially improves response rates compared to standard cold applications.
