Scientist - Hospital Patient Monitoring

Job Title

Scientist - Hospital Patient Monitoring

Philips Hospital Patient Monitoring (HPM) develops solutions that help caregivers monitor patients reliably and continuously, enabling timely clinical decisions and safer care. At HPM Research
, we conduct applied scientific research on smart monitoring and measurement solutions, driven by deep customer insights and unmet clinical needs. We do this in close collaboration with clinical stakeholders.

Your role: You will be part of the HPM Research team, working on innovative solutions. In this role, you will create and validate novel algorithms for next-generation smart monitoring and measurements, turning physiological data into reliable metrics and algorithms that can be translated into meaningful monitoring features.

• Analyze physiological time-series signals (filtering, artifact detection, signal quality, and feature extraction).
• Develop, implement, and test novel algorithms (from prototype to reusable code).
• Set up data-collection studies, and curate datasets for analysis.
• Define datasets and experiments: inclusion/exclusion criteria, labels/ground truth, and basic data preprocessing steps.
• Validate algorithm performance with agreed metrics (e.g., sensitivity/specificity, false alarm rate) and analyze failure modes and edge cases.
• Document methods and results (short reports/slides) and clearly state conclusions, assumptions, and limitations.
• Collaborate with scientists, engineers, and clinical stakeholders to translate findings into algorithms.

• Master or PhD in Biomedical Engineering, Electrical Engineering, Applied Physics, Computer Science, or equivalent experience, with a biomedical/biophysical focus.
• Strong experience in time-series physiological signal processing and analysis.
• Comfort with data analysis, algorithm development, (bio) statistics, and applied machine learning.
• Strong coding skills in Python or MATLAB;
  Python is preferred.
• Interest in human physiology and how physiological systems translate into measurable signals.
• Ability to translate questions into a clear analysis plan and validate results (assumptions, limitations, reproducibility).
• Clear communication—writing concise summaries and presenting findings to engineers, clinicians, or product stakeholders.
• Enjoy collaborating in a multidisciplinary team and asking for feedback early.
• End-to-end thinking: from clinical need to research question to data collection, preprocessing, and analysis.
• Willing to travel internationally on occasion.