Epigenetics, Stem Cells and Artificial Intelligence
Summer Internship On Epigenetics Without Barriers
About the Program
Join the Helmholtz Munich Summer Internship: Epigenetics Without Borders
Step into the world of cutting-edge life science research where AI, stem cells, environment, and chromatin intersect.
This international program offers highly motivated undergraduate and first-year master’s students a 2-month hands-on research experience in wet and/or dry labs (July-August). Work alongside leading scientists on projects that shape the future of health.
You’ll gain practical skills in biochemistry, molecular biology, imaging, stem cell biology, and computational approaches including AI, tailored to your host lab’s expertise.
Don’t miss this chance to explore the dynamic field of epigenetics and lifelong health—and take your first step toward a career in science.
Applications open late 2026
What we Offer
Diverse Projects
Dive into exciting research—from fundamental epigenetic mechanisms to cutting-edge applications like deep learning and spatial transcriptomics.
Real-World Experience
Step into the daily life of a leading research institution and gain hands-on skills in both wet and dry lab environments.
Collaboration with Experts
Work alongside world-class scientists on groundbreaking projects during an intensive 2-month program.
Career Development
Especially valuable for Master’s students: this internship can open doors for continued research in the host lab (subject to mutual agreement).
Support & Benefits
Accommodation and a monthly allowance.
What You'll Learn
- How to think critically and ask complex scientific questions
- How to design and execute productive experiments
- How to develop and apply advanced computational and machine-learning approaches
- How to present and discuss your data with leading experts in epigenetics
In previous years, Interns have undertaken research in the following thematic areas:
Histone modifications
Environmental stress
Nuclear architecture
Image processing
Metabolic diseases
Cell fate decisions
Deep learning
AI
Totipotency
Spatial transcriptomics