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Open nowPosted 12 days ago

Recognised Researcher (R2)

EURES job mobility portal612,521 open roles

Where
Arnhem/Nijmegen, Netherlands
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Your applicationOpen nowRecognised Researcher (R2)EURES job mobility portal · Arnhem/Nijmegen, Netherlands

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The clock on this job

Early applications get read.

10.7% of postings close within 7 days. Measured by our own scanner across the market. EURES job mobility portal postings stay open a median of 9 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.4%3 days
  3. 10.7%7 days
  4. 16.1%14 days
  5. 34.1%30 days
This job: posted 12 days ago

EURES job mobility portal median: 9 days open

The posting

Logo of EURAXESS - JOB - Netherlands - Posted on: 2 October 2026 2 Oct 2026 Radboud University Medical Center (Radboudumc) Research Field Engineering » Biomedical engineering Medical sciences » Medicine Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Type of Contract Hours Per Week Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? Artificial intelligence is increasingly used in medical imaging, but the evidence required to demonstrate that these systems are safe and reliable is still evolving. Synthetic imaging data may help address limited access to representative clinical datasets, for example by augmenting training data or supporting model evaluation. However, it is currently unclear under which conditions synthetic data can be considered sufficiently representative, unbiased, privacy-preserving, and scientifically valid for (premarket) regulatory purposes. In this PhD project, you will investigate when and how synthetic medical imaging data can be used as evidence in the development and regulatory evaluation of medical device AI. The project is part of COMPASS4MD, a Horizon Europe consortium developing new methodologies for evaluating clinical evidence for medical devices. Your work will combine technical evaluation of synthetic imaging data with regulatory science and research methodology. You will study how synthetic imaging data are currently used in research and regulatory submissions, experimentally assess their quality and fitness for different purposes, and translate these findings into evidence requirements for regulatory use. You will work on questions such as: - How representative are synthetic images compared with real clinical data? - Which metrics are meaningful for assessing fidelity and clinical validity? - How do privacy protection, bias and representative...

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