Summer Intern: Digital Signal & Imaging AI

Johnson & Johnson Co.

Zug

On-site

CHF 20,000 - 36,000

Full time

6 days ago
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Benefits offered by this job

Remote work possibilities

Job summary

Johnson & Johnson is offering an internship/co-op position within the DDSAI data science group. You will join a team of data scientists to tackle research questions at the AI-healthcare frontier.

The role includes handling wearable sensor data, neuroimaging data, and developing machine learning models to derive digital biomarkers and insights. European locations include Beerse, Leiden, and Zug, with remote options possible.

Qualifications

  • Currently pursuing a PhD 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

Responsibilities

  • Collaborate with the J&J DDSAI organization to apply advanced data science and analytics to key research questions.
  • Work on cutting-edge problems at the intersection of AI and healthcare with a dynamic team.
  • Contribute to processing and analysis of wearable sensor and neuroimaging data and model development.

Skills

AI/ML knowledge
Python
Data analysis
Communication

Education

Pursuing a PhD in Biomedical Engineering, Electrical Engineering, Neuroscience, Applied Mathematics, Statistics, Data Science

Tools

PyTorch

Job description

Johnson & Johnson is offering an internship/co-op position within the DDSAI data science group. You will join a team of data scientists to tackle research questions at the AI-healthcare frontier.

The role includes handling wearable sensor data, neuroimaging data, and developing machine learning models to derive digital biomarkers and insights. European locations include Beerse, Leiden, and Zug, with remote options possible.

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