Summer intern, Digital Signal/ Imaging AI

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.

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Job Description:

In this role, you will work with colleagues in the J&J Innovative Medicine R&D Data, Data Science, and AI (DDSAI) organization and partner with key businesses across J&J Innovative Medicine 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 AI and healthcare. 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, processing and analysis of wearable sensor and neuroimaging data, development of machine learning models for digital biomarker discovery, validation of digital health endpoints, generation of insights from real-world physiological and behavioral data, modeling and prediction of disease severity and progression, and discovering of disease subtypes. Interns could be located out of our US locations in San Diego, San Francisco, Titusville, Raritan, Spring House, Boston, or out of Europe locations in Beerse (Belgium), Leiden (The Netherlands), Zug (Switzerland) as well as remote.

Minimum qualifications:

• Currently pursuing a PhD degree in Biomedical Engineering, Electrical Engineering, Neuroscience, Applied Mathematics, Statistics, Data Science, or a related quantitative discipline.
• Strong working knowledge of AI and machine learning.
• Advanced in Python or R
• Strong skills in predictive modeling, statistics, and analysis of large datasets.
• Strong technical communication and presentation skills.
• Basic knowledge of data cleaning and data quality

Preferred qualifications:

Experience in one or more of the following:

• Experience with processing and analyzing sensor, wearable device, clinical records, and/or medical imaging data.
• Proficiency with pytorch.
• Experience with semi-supervised and/or self-supervised learning.
• Experience with Foundation Models

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.

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 & 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,  external applicants please contact us via https://www.jnj.com/contact-us/careers . Internal employees contact AskGS to be directed to your accommodation resource.

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