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:

CH002 Gubelstrasse, Zug

Job Description:

Johnson & Johnson is currently seeking a PhD Summer Intern to join our Computer Vision Team, R&D Data Science located in Zug, Switzerland.

Join us to advance the future of human health and take the first steps toward building a career with a purpose.

Position Overview - Tasks & Responsibilities:

As a summer intern you will be a part of our R&D Data Science team and support our scientists and engineers in developing the next generation AI tools for Inflammatory Bowel Disease (IBD) projects for Immunology.

Tasks include but are not limited to

a) Explore existing uncertainty estimation techniques for regression problems in deep learning, including Bayesian approaches, ensemble methods, and evidential deep learning.

a) Integrate uncertainty estimation techniques into regression models for disease estimation in videos.

b) Benchmark pipeline against existing baselines, such as Monte Carlo Dropout, 3. Deep Ensembles, and Bayesian Neural Networks.

a) Exploration of Advanced Methods:

b) Evidential Deep Learning for regression.

c) Epistemic Neural Networks for better quantification of epistemic and aleatoric uncertainty.

a) Train and evaluate models on endoscopy datasets.

b) Compare the performance and reliability of different uncertainty estimation techniques.

c) Analyze the correlation between uncertainty and clinical outcomes.

a) Integrate uncertainty estimation methods into existing AI pipelines for clinical trials.

b) Collaborate with clinical teams to interpret results and refine methods for real-world deployment.

c) Draft publication.

Qualifications - Education and Experience:

• Currently enrolled in a doctoral program in data science or applied AI/ML at a Swiss university.

• Experience in medical imaging and developing applied AI models for medical applications.

Qualifications - Skills:

• Demonstrated experience driving research in and applying Computer Vision techniques (e.g., Transformers, CNNs, RNNs, GANs).

• Demonstrated experience on state-of-the-art techniques for computer vision (e.g. foundational models, transformers).

• Proficiency in Python.

• Extensive experience with traditional Computer Vision applications, such as OpenCV, object detection, edge detection, image segmentation.

• Experience with machine learning algorithms, including random forest, SVM, boosting, neural networks, etc.

• Strong publication record and ability to effectively communicate technical work to a wide audience.

• Interest in exploring the areas of applied AI/Machine learning and Data Science for medical applications.

• Fluent in English

• Basic statistical knowledge.

• Strong communication & interpersonal skills.

• Ability to work in a matrix organization and participate effectively both independently and as part of multiple teams.

• Capacity to work under strict timelines.

Our Offering:

• 4 months full time internship in an international healthcare company to grow your professional experience, start date 1st July 2025

• Exciting and intensive insight into one of the largest Pharma companies in the world

• Great team and excellent sense of belonging

• Flexible working conditions with the opportunity of 40% remote work if the job allows