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Scientist - Hospital Patient Monitoring

Posted 2 Jun 2026
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Work experience
2 to 5 years
Full-time / part-time
Full-time
Job function
Degree level
Required language
English (Fluent)

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At Philips Hospital Patient Monitoring (HPM), we develop 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.

You will

  • 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.

You're the right fit if:

  • You have a Master or PhD in Biomedical Engineering, Electrical Engineering, Applied Physics, Computer Science, or equivalent experience, with a biomedical/biophysical focus.
  • You have strong experience in (time-series) physiological signal processing and analysis.
  • You are comfortable with data analysis, algorithm development, (bio)statistics, and applied machine learning.
  • You have strong coding skills in Python or MATLAB; Python is preferred.
  • You have an interest in human physiology and how physiological systems translate into measurable signals.
  • You can translate questions into a clear analysis plan and validate your results (assumptions, limitations, reproducibility).
  • You communicate clearly—writing concise summaries and presenting findings to engineers, clinicians, or product stakeholders.
  • You enjoy collaborating in a multidisciplinary team and asking for feedback early.
  • You think end-to-end: from clinical need to research question to data collection, preprocessing, and analysis.
  • You are willing to travel internationally on occasion.

Signals of fit

  • You learn fast, are curious, and proactively build new skills.
  • You think critically and translate results into clear conclusions, including risks and limitations.
  • You value scientific rigor, reproducibility, and transparent reporting.
  • You provide decision-ready recommendations—not just plots and metrics.
  • You take ownership of small work packages and ask for feedback early to iterate quickly.

Signals of mismatch

  • You prefer working only with fully curated datasets and are not interested in sensing, data collection, or validation strategy.
  • You are uncomfortable with scientific discussion, peer review, or challenging assumptions.
  • You are looking primarily for a project management role rather than hands-on scientific/technical work.

How we work together

We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.

Philips is a leading health technology company focused on improving people’s lives across the health continuum – from healthy living and prevention, to diagnosis, treatment and home care. Applying advanced technologies and deep clinical and consumer insights, Philips delivers integrated solutions that address the Quadruple Aim: improved patient experience, better health outcomes, improved staff experience, and lower cost of care.

Manufacturing
Amsterdam
Active in 100 countries
11,000 employees
60% men - 40% women
Average age is 39 years