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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 https://www.jnj.com

Job Function:

Career Programs

Job Sub Function:

Non-LDP Intern/Co-Op

Job Category:

Career Program

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, Spring House, Pennsylvania, United States of America

Job Description:

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 https://www.jnj.com/.

Fueled by innovation at the intersection of biology and technology, we’re developing the next generation of smarter, less invasive, more personalized treatments.

Your unique talents will help patients on their journey to wellness. Learn more at https://www.jnj.com/medtech

Job Description:

The Computer Vision team at Johnson & Johnson Innovative Medicine is seeking a knowledgeable, self-motivated, and creatively inclined graduate student with a strong interest in computer vision, deep learning, and medical image analysis for a 10-12 week summer research internship. In this role, you will participate in training and fine-tuning foundation model for radiology image segmentation, enhancing the downstream segmentation accuracy and efficiency by using task-specific active learning or semi-supervised learning techniques.

This internship offers the opportunity to work within a cross-functional team in a pharmaceutical environment. In addition to gaining technical exposure through the various projects the team is undertaking, you will also gain valuable insights into how algorithms are developed to support clinical trials under the mentorship of experienced scientists, while contributing to initiatives aimed at improving global health.

Responsibilities:

• Design, develop, implementand validateinnovative deep learning solutions addressing high-priority computer vision challenges in medical imaging.

• Collaborate closely with cross-functional teams of scientists, engineers, and clinicians to advance algorithm and product development to improve project outcomes.

• Clearly communicate complex technical methodologies and present findings to diverse audiences and stakeholders to support informed decision-making.

• Prepare and draft manuscripts outlining development methodologies to contribute to the scientific community.

Qualifications

• Holding or actively pursuing a PhD or Masters in a field related to deep learning and computer vision, such as computer science, medical informatics, biomedical engineering, electrical engineering, or a related discipline.Master’s degree with equivalent experience will also be considered.

• Strong publication record with the ability to effectively communicate technical work to a broad audience. Publications in conferences such as CVPR, ICLR, ICCV, ICML, MICCAI, ACL, and NEURIPS are preferred but not mandatory.

• Demonstrated experience in computer vision research, including the application and development of AI methods and optimization of machine learning models is required.

• Strong programming skills in Python and PyTorch.

• 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.

Preferred Qualifications:

• Demonstrated foundation in applying deep learning techniques for computer vision and image analysis, particularly in object detection and image segmentation.

• Expertise in active learning or semi-supervised learning methods is highly preferred.

• Experience with vision foundation model.

• Experience with X-ray images and other medical imaging modalities.

• Familiarity with and exposure to drug discovery and clinical development processes.

• Experience collaborating with healthcare professionals.

• Knowledge of relevant disease biology, particularly in immunological diseases.

Our Offering:

• 3-month full-time internship working within a cross-functional team in a pharmaceutical environment.

• Internship dates will be from June to August/September

• Gain technical exposure through various projects the team is undertaking.

• Acquire valuable insights into algorithm developmentin support for clinical trials under the mentorship of experienced scientists.

• Contribute to initiatives aimed at improving global health.

• Flexible working conditions with fully remote options available.

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson and Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, please email the Employee Health Support Center (ra-employeehealthsup@its.jnj.com) or contact AskGS to be directed to your accommodation resource.