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AI Research Engineer

ScreenPoint Medical

Nijmegen, NetherlandsJobPosted 6mo agoStill listed 2 days ago

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At a glance

Compensation
No compensation found
Location
Nijmegen, Netherlands
Work Authorization
Not specified

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Requirements

Credentials this posting asks for.

Master's degree

Job overview

ScreenPoint Medical seeks an enthusiastic AI Research Engineer to join its Innovation team, developing foundation models and downstream AI solutions for breast cancer imaging. The role involves collaborating with clinical experts, designing robust models, and advancing medical imaging AI in a fast‑growing, mission‑driven environment.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningBiomedical EngineeringComputer ScienceDeep LearningClinical ResearchCamera CalibrationVision Transformer NetworksVision-Language ModelsFoundation ModelsMultimodal Data HandlingModel EvaluationCalibrationRobustnessSubgroup Performance AnalysisPythonDeep Learning FrameworksLinux Environments

Qualifications

MSc or PhD in Computer Science or Machine Learning or Biomedical Engineering or Applied Mathematics or Physics or Related Technical Field5 Years Experience Developing AI or Machine Learning Models in Medical Imaging or Clinical Research Context

Full job description

We are always interested in connecting with exceptional AI Research Engineers. This vacancy is part of our talent pool, meaning we may not have an immediate opening, but we would love to get in touch for future opportunities within our Innovation team.

In the fight against breast cancer, every medical image is an opportunity: to unlock insight, to uncover risk, to embody health, to empower life. ScreenPoint’s Transpara Breast AI delivers unmatched precision for breast radiologists and helps define personalized care pathways for every woman we serve. Make your mark as part of The Breast AI Company.

We are looking for an enthusiastic and motivated AI Research Engineer to strengthen our Innovation team in building the foundation of ScreenPoint’s future AI models. For this role we look for someone who can develop foundation models and has experience with state-of-the-art methods (vision transformer networks, vision-language models). These methods will be used in downstream applications to solve a broad range of clinically relevant problems in breast cancer care in close collaboration with clinical experts.

You’ll be part of a highly motivated and ambitious group of experts in breast imaging, artificial intelligence and clinical research, who work closely together in an informal atmosphere to make our mission become a reality. You will work with a broad range of technologies and have the opportunity to learn and grow on a daily basis.

Your responsibilities

  • Design and implement downstream AI models that operationalize clinical endpoints using outputs from foundation models.
  • Translate clinical study designs and outcome definitions into clear modeling tasks and evaluation frameworks in collaboration with Clinical Scientists.
  • Define and apply consistent modeling and evaluation approaches across multiple biomarkers and imaging modalities.
  • Collaborate closely with the AI Algorithm Lead to ensure robust integration between foundation models, MLOps infrastructure, and downstream biomarker models.
  • Guide and review modeling approaches developed by AI Research Scientists, providing technical feedback and mentorship.
  • Perform in-depth model analysis, including calibration, subgroup performance, and failure-mode assessment.

Experience and skills

  • MSc or PhD in Computer Science, Machine Learning, Biomedical Engineering, Applied Mathematics, Physics, or a related technical field
  • At least 5 years of experience developing AI or machine learning models in a medical imaging or clinical research context
  • Proven ability to translate clinical or scientific questions into appropriate modeling approaches (e.g. classification, risk prediction, longitudinal modeling)
  • Experience working with multimodal data (e.g. imaging combined with clinical or pathology data)
  • Strong understanding of model evaluation, calibration, robustness, and subgroup performance in real-world datasets
  • Familiarity with foundation models and downstream fine-tuning or adaptation strategies
  • Proficiency in Python and deep learning frameworks, and experience working in Linux-based environments

Preferred qualifications

  • Experience in NLP with LLMs or VLMs

About us ScreenPoint Medical is a leading company that develops and markets breast image analysis and cutting edge machine learning applications and services. Our product Transpara improves breast cancer survival rates by detecting cancers earlier so that treatment can be more effective and less invasive.

Do you want to help us build an innovative solution to improve health worldwide? And do you want to be part of an ambitious and fast-growing team who help you develop your career further? Please apply using the application button.

Providing a Certificate of Conduct (VOG) or background check is part of our application procedure. Questions about the contents of the vacancy or the recruitment process at ScreenPoint Medical? Please send an email to [email protected].

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