What are the responsibilities and job description for the Data Science Graduate Intern, AI/ML (Predictive/Generative Modeling) position at J&J Family of Companies?
R&D Data Science & Digital Health DSAI Intern Summer 2025
Caring for the world, one person at a time has inspired and united the people of Johnson & Johnson for over 130 years. We embrace research and science bringing innovative ideas, products and services to advance the health and well-being of people. Employees of the Johnson & Johnson Family of Companies work with partners in health care to touch the lives of over a billion people every day, throughout the world.
With $81.6 billion in 2018 sales, Johnson & Johnson is the world's most comprehensive and broadly based manufacturer of health care products, as well as a provider of related services, for the consumer, pharmaceutical, and medical devices and diagnostics markets. There are more than 250 Johnson & Johnson operating companies employing approximately 130,000 people in 60 countries throughout the world.
Calling all big thinkers and world-changers who want to drive their careers forward across more than 250 leading businesses in consumer, pharmaceutical and medical technology. If you have the talent and desire to touch the world, Johnson & Johnson has the career opportunities to help make it happen.
Position Components
In this role, you will work with colleagues in the JNJ Innovative Medicine R&D Data Science & Digital Health organization and partner with key businesses across JNJ Innovative Medicine (formerly Janssen) to apply advanced data science and analytics to answer key research questions. As an intern, you will get the opportunity to work on cutting-edge problems at the intersection of artificial intelligence and drug discovery. You will be a member of a dynamic team comprising data scientists and subject matter experts to create and iterate on data science solutions. Projects include, but are not limited to, developing, and applying predictive and generative artificial intelligence methods for molecular property prediction and generation with the ultimate goal of drug discovery. Interns could be located out of our US locations in San Diego, San Francisco, Titusville, Raritan, Spring House, Boston as well as remote.
Qualifications
Minimum qualifications :
Currently pursuing a Masters, or PhD degree in Data Science, Computer Science, Electrical Engineering, Statistics, or related quantitative discipline.
Strong working knowledge of machine learning with demonstrated research experience, as evidenced by publications, public code contributions, etc.
Proficiency in Python and hands-on experience with Deep Learning frameworks such as PyTorch or TensorFlow to tackle scientific problems.
Strong technical communication and presentation skills.
Ability to understand and write academic research papers.
Preferred qualifications :
Experience in one or more of the following :
Extensive research experience working with sequence models (e.g.- with Large Language Models (LLMs)) and / or Graph Neural Networks (GNNs).
Familiarity with Equivariant Geometric Deep Learning and / or state space sequence modelling is a plus.
Knowledge and interest in drug discovery and experience working with drug discovery datasets, including graph, sequence, and / or structure-based data is a plus.
Others :
- 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. Students currently on CPT, OPT, or STEM OPT usually requires future sponsorship for long term employment and do not meet the requirements for this program unless eligible for an alternative long-term status that does not require company sponsorship.
Responsibilities :
Development and evaluation of predictive and generative machine learning algorithms to analyze molecular datasets for drug discovery.
Collaborate closely with other machine learning scientists, computational biologists and chemists to develop and execute the research project.
Document and disseminate research findings internally and externally (e.g.- publishing in top-tier ML conferences / journals).
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
