Data Scientist Intern

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:
Zug, Switzerland

Job Description:

Johnson & Johnson Innovation Medicine focuses on discovering and developing innovative solutions to address critical unmet medical needs across multiple therapeutic areas.

We are seeking a highly motivated and innovative Data Science Intern to support our research and development initiatives focusing on multimodality.

This internship offers a unique opportunity to work with our AI/ML team on building a multimodal framework based on high dimension biology data, thereby driving the development of an innovative application.

The primary objective of this internship is to explore the integration of various modalities in multimodal learning.

By effectively designing this framework, we aim to enhance our understanding of the materials utilized in our projects, strengthening decision-making processes and advancing drug discovery efforts.

This internship can also be pursued as a Master's thesis project, providing an excellent opportunity for academic integration.

Key Responsibilities:


* Collaborate with the AI/ML team to develop and implement multimodal learning frameworks.


* Analyze and aggregate different modalities through biological insights and maximize benefits from multimodal learning.


* Present analytical findings to cross-functional teams, contextualizing results within broader project goals.


* Draft technical papers for high impact conferences and/or journals

Qualifications - External


* Currently pursuing or recently completed a Ph.D.

in Electrical Engineering, Computer Science, Statistics, Applied Mathematics, or a related field.


* Strong Master's degree students can also pursue this role as their thesis project.


* Extensive hands-on experience in AI/ML research and applications including Computer Vision, NLP, Geometry learning, or related fields.


* Experience in drug design, medical imaging, or omics is a plus.


* Strong publication record (CVPR, ICCV, ICLR, NeurIPS, ICML, MICCAI, ACL, etc.)


* Proficiency in Python, and experience with AI frameworks like PyTorch or TensorFlow.


* Strong communication skills to effectively communicate and collaborate in a cross-functional setting