PhD Candidate in Explainable Machine Learning for Single-Cell Biology
Develop interpretable AI models to unlock biological insights from single-cell omics data in Amsterdam’s interdisciplinary research environment.
Best for:Best for MSc graduates in bioinformatics, data science, or AI with hands-on experience in Python-based machine learning and a keen interest in single-cell biology and computational methods.
Overview
This PhD position at the University of Amsterdam focuses on advancing explainable machine learning to analyze single-cell (multi-)omics data by integrating biological knowledge into models. The successful candidate will work within the Biosystems Data Analysis group at the Swammerdam Institute for Life Sciences, bridging computer science, mathematics, and biology. The project aims to create interpretable-by-design AI tools applicable across diverse biological datasets, addressing challenges in understanding gene regulation, disease mechanisms, and cellular communication. The role offers collaboration with biologists in immunology, cancer research, and beyond, alongside access to high-performance computing infrastructure. Ideal candidates should combine a strong foundation in machine learning with curiosity about biological systems and a passion for interdisciplinary research.
What you'll do
- Develop novel interpretable machine learning algorithms for analyzing single-cell (multi-)omics data, integrating biological knowledge into models.
- Conduct in silico experiments to test and validate new methodologies on diverse biological datasets.
- Collaborate closely with biologists across disciplines (e.g., immunology, cancer biology) to translate computational insights into biological discoveries.
- Present research findings at national and international scientific conferences.
- Participate in peer-reviewed journal and conference manuscript preparation, taking a leading role in writing.
- Engage in the University of Amsterdam’s PhD training program, including coursework and academic development.
- Assist in teaching and supervising Bachelor’s and Master’s students in computational biology and related fields.
Requirements
Degree required: Master of Science (MSc) in Bioinformatics, Artificial Intelligence, Data Science, Biostatistics, or a closely related discipline
Degree offered: PhD
Language: English; proficiency at a level suitable for academic research and collaboration
Instruction: English
- Proven experience training machine and deep learning models, preferably using Python
- Strong foundation in machine learning and artificial intelligence principles
- Basic understanding of biological concepts or willingness to learn computational methods for biology
- Fluency in English (written and spoken) for academic collaboration and communication
- Ability to work independently and collaboratively in an interdisciplinary team
- No formal eligibility restrictions beyond the required degree
- Open to candidates from diverse academic and professional backgrounds
Funding & terms
How to apply
Deadline: 2026-10-13
Applicants must submit a detailed CV (with monthly work/education details), a letter of motivation, and the contact information for two references who can provide letters of recommendation. All documents except the CV should be combined into a single PDF file and submitted via the university’s online application portal.
- CV with detailed monthly work/education timeline
- Letter of motivation
- Names and email addresses of two references for recommendation letters
Contact
Stavros Makrodimitris· Supervisor
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