About the job
Data Science and Digital Health (DSDH) function within Johnson & Johnson Innovative Medicine Research & Development, is recruiting for the role of Postdoctoral Scientist AI/ML & DH. The location for this position is Cambridge, MA; Titusville, NJ; Spring House, PA or Beerse, Belgium
Responsibilities
Analyze data from wearable sensors to develop digital biomarkers using methodologies from signal processing and AI.
Prepare and process raw sensor data streams to extract clinically relevant and novel features.
Build novel or enhance existing AI algorithms or time-series models for digital endpoint development and validation.
Build sensor data analysis and modeling pipelines to develop re-usable software assets.
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.
Communicate results to internal stakeholders and external partners through project reports and peer reviewed research publications
Qualifications
Minimum
A recent 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.
Preferred
Familiarity with drug discovery and the clinical development process.
Hands-on experience with digital endpoint/biomarker validation frameworks