Postdoctoral Scientist Data Science Ai/ml & Dh

Johnson & Johnson Johnson & Johnson · Pharma · Neuss, North Rhine-Westphalia, Germany

This role focuses on analyzing data from wearable sensors to develop digital biomarkers and AI algorithms for digital endpoint development and validation within Johnson & Johnson's Innovative Medicine Research & Development. The scientist will process sensor data, extract features, build and enhance AI/time-series models, and create data analysis pipelines, publishing results.

What you'd actually do

  1. Analyze data from wearable sensors to develop digital biomarkers using methodologies from signal processing and AI.
  2. Prepare and process raw sensor data streams to extract clinically relevant and novel features.
  3. Build novel or enhance existing AI algorithms or time-series models for digital endpoint development and validation.
  4. Build sensor data analysis and modeling pipelines to develop re-usable software assets.
  5. Partner with cross-functional teams to execute on developing, adapting, and delivering digital health solutions. This includes defining “what” and “why” particular digital phenotype needs to be measured, developing analytical strategy and designing specific experiments.

Skills

Required

  • Ph.D. degree within 3 years in computer science, electrical engineering, biomedical engineering, or related discipline
  • Extensive experience in analyzing high frequency data from wearable biosensors (e.g., accelerometer, ECG, PPG)
  • Strong background and proven experience in developing or implementing advanced state of the art AI and signal processing methods
  • Experience with large scale data processing and integrating multi-modal datasets
  • Proficiency in one or more programming languages such as Python, R, MATLAB and writing re-usable and well documented code
  • Demonstrated scientific excellence as measured by publications and presentations
  • Excellent interpersonal, communication, and presentation skills
  • Ability to work in a dynamic and collaborative environment

Nice to have

  • Familiarity with drug discovery and the clinical development process
  • Hands-on experience with digital endpoint/biomarker validation frameworks

What the JD emphasized

  • Extensive experience in analyzing high frequency data from wearable biosensors
  • Strong background and proven experience in developing or implementing advanced state of the art AI and signal processing methods
  • Demonstrated scientific excellence as measured by publications and presentations

Other signals

  • develop digital biomarkers using methodologies from signal processing and AI
  • extract clinically relevant and novel features
  • Build novel or enhance existing AI algorithms or time-series models
  • Build sensor data analysis and modeling pipelines