2026 AI/ML & NMR Structural Verification Intern (PhD)

Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.

Job Description

2026 AI/ML & NMR Structural Verification Intern Overview

Envision spending your summer working with energetic colleagues and inspirational leaders, all while gaining world-class experience in one of the most dynamic organizations in the pharmaceutical industry. This is a reality for AbbVie Interns.

The AI/ML & NMR Structural Verification Intern will interact closely with Data Sciences and Nuclear Magnetic Resonance (NMR) team members to develop an AI/ML workflow using a DP4/DP5 model coupled with Gaussian calculation for NMR structural identification. The goal of the project is to streamline and accelerate the structure verification process. 

Key responsibilities include:

• Evaluate the published AI-based models such as DP4/DP5-AI workflow
• Test the workflow on a set of compounds with existing NMR data to assess its reliability
• Improve and enhance the calculation of NMR shifts by leveraging advanced DFT calculations and Bayesian inference
• Design a robust, scalable screening template that integrates the optimized AI model into the NMR identification processes 

Qualifications

Minimum Qualifications 

• Currently enrolled in university, pursuing a PhD in Data Science, Computer Science, Computational Chemistry, Chemistry, or other related field (Chemistry is preferred)
• Must be enrolled in university for at least one semester following the internship
• Experience with Python, HPC, SQL, and Gaussian calculation
• Strong written and verbal communication skills and the ability to interact effectively with interdisciplinary scientists and engineers
• High attention to detail, creativity in proble