Internship: Data Science
Full-time
Amsterdam, Netherlands
Posted on Oct 12, 2026
📍 Location: Amsterdam
🕒 Timing: September/October, 6-9 months internship
💼 Full-time
🕒 Timing: September/October, 6-9 months internship
💼 Full-time
About the internship
Nostics is developing a next-generation diagnostic platform for rapid detection and identification of bacterial infections. As part of a Eurostars project, we are working on using our technology for bloodstream infection diagnostics, combining advanced sensing technologies with data-driven analysis to enable faster and more informed clinical decisions.
We are looking for a Data Science Intern to develop as well as use existing data pipelines and machine learning models on data generated from a technical evaluation study with two European hospitals.
What You’ll Do
- Process and analyze spectral or high-dimensional biological data generated from clinical blood cultures
- Support development and evaluation of machine learning models for classification and pattern recognition
- Explore feature extraction and dimensionality reduction approaches (e.g. PCA, UMAP, clustering methods)
- Assist in building reproducible data pipelines for preprocessing, annotation, and model training
- Contribute to benchmarking and validation of models against experimental datasets
- Help document workflows and results for internal use and project reporting (Eurostars)
Who you are
- Enrolled in an MSc in Data Science, Bioinformatics, Biomedical Engineering, Computer Science, or a related field
- Strong foundation in Python (e.g. NumPy, pandas, scikit-learn)
- Familiarity with machine learning methods and data analysis workflows
- Strong analytical thinking and ability to structure and communicate results clearly
Bonus
- Experience with spectral data, signal processing, or life sciences data
- Experience with handling complex datasets (biological or otherwise)
- Comfortable working in a research-driven, exploratory environment
- Familiarity with deep learning frameworks (e.g. PyTorch, TensorFlow)
- Interest in diagnostics, microbiology, or healthcare applications
What you’ll learn
- How to apply machine learning to real-world biomedical data in a regulated context
- Practical challenges of working with experimental and clinical datasets
- How early-stage diagnostic technologies are developed and validated
- How interdisciplinary teams (biology, engineering, data science) collaborate
- How data-driven insights translate into clinically relevant outputs
Interested?
Apply via the button below!
