Intern-AI/ML in Antibody Developability Models

Johnson & Johnson Innovative Medicine • San Diego, CA

1d • $27 - $59 • Onsite

About The Position

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Johnson & Johnson Innovative Medicine is recruiting for a Summer Intern - AI/ML in Antibody Developability Models position in the Drug Discovery Data Science, In Silico Discovery (ISD) group in La Jolla, CA. The Intern term is from June to August, 2026. Full time requirement (40 hours per week). Job Description The Drug Discovery Data Science group within the In Silico Discovery (ISD) organization in La Jolla, CA is seeking a current PhD student for a 10-12 week Summer research internship. We are looking for a knowledgeable, self-motivated, creative, and multi-skilled graduate student with a strong interest in machine learning, data science, computational biology, and biotherapeutics discovery. In this role, the intern will design and implement machine learning frameworks that leverage public protein property datasets alongside internal experimental data to improve predictive models. Thermostability and related properties will be key areas of focus.

Requirements

• Completion of Undergraduate Freshman year at an accredited University is required.
• Have a cumulative GPA of 2.8 or higher, which is reflective of all college coursework.
• PhD student in computational biology, biophysics, machine learning, data science, or related field.
• Demonstrated experience in deep learning with proficiency in Python and PyTorch.
• Familiar with protein language models and key structural determinants of protein stability.
• Candidates must have authorization to work in the U.S.
• The individual should be able to work onsite at our La Jolla campus during the whole internship period.
• Permanently authorized to work in the U.S., must not require sponsorship of an employment visa (e.g., H-1B or green card) at the time of application or in the future.

Nice To Haves

• Experience with transfer learning or working with pretrained deep learning models preferred.
• Familiarity with antibody structure and function is preferred.
• Strong communication, problem-solving, and collaboration skills.

Responsibilities

• Collecting and curating large public datasets.
• Developing and engineering features by integrating sequence embeddings from state-of-the-art protein language models and structure-derived descriptors, as well as benchmarking alternative feature sets.
• Developing deep learning models to capture general physicochemical stability patterns.
• Applying transfer learning by fine-tuning pretrained models on internal antibody thermostability datasets and rigorously evaluating predictive performance.
• Publication is encouraged.

Benefits

• Co-Ops/Interns are eligible to participate in Company sponsored employee medical benefits in accordance with the terms of the plan.
• Co-Ops and Interns are eligible for the following sick time benefits: up to 40 hours per calendar year; for employees who reside in the State of Washington, up to 56 hours per calendar year.
• Co-Ops and Interns are eligible to participate in the Company’s consolidated retirement plan (pension).

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: Ph.D. or professional degree