We are looking for a Deep Learning Engineer to join our team!
This Deep Learning Engineer will be part of the AI team within the R\&D department. In this role, the Deep Learning Engineer should have excellent knowledge and experience working with neural networks for (medical) image analysis. The aim is to create novel products based on the analysis of digital microscopy images of tumor tissue, combined with genomics and transcriptomics data, for instance, to predict the risk of cancer recurrence. The Deep Learning Engineer works in a team of (data) scientists and bioinformaticians and with partners from academia and industry.
Main duties for this position:
o Analyze and integrate large diverse clinical, molecular and imaging datasets to extract insights, and drive research opportunities.
o Apply deep learning, statistical and machine learning methods to analyze large, complex data sets.
o Communicate highly technical and scientific results and methods clearly
o Aid in setting up A.I. / Big Data infrastructure
o Development and productionizing of artificial intelligence and machine learning models for image analysis and genomic/transcriptomic data.
o Support grant applications and management, writing of scientific reports / manuscripts / patents
o Interact cross-functionally with a wide variety of people and teams
o Collaborate with commercial and academic partners
o Interrogate analytical results for robustness, validity, and out of sample stability
o Document, summarize, and present your findings to a group of peers and stakeholders.
Minimum requirements:
o A masters/PhD degree in machine learning, computer vision, computer science, physics or mathematics
o 3+ years’ of relevant experience in AI, Image Analysis and Deep Learning
o Experience working with genomic, transcriptomic, clinical, or imaging data
o Experience with programming / scripting languages such as Python
o Experience with deep learning frameworks such as PyTorch / JAX
Nice to have:
o Experience taking ML from research prototype to production deployment (ownership across data, training, evaluation, monitoring)
o Familiarity with CI/CD for ML codebases
o Exposure to foundation models, deep learning for pathology, and domain adaptation
o Data Engineering for ML (data versioning, preprocessing, Whole Slide Images)
o Good software development hygiene (code reviews, debugging, performance profiling)
For this role, we only consider candidates who are already based in the Netherlands. We will start screening applicants from 2 February onwards!