About the summer school

“Hands-on summer school: Fundamentals in integrating synthetic biology, data, AI” is a three-day summer school designed to introduce participants to the emerging intersection of synthetic biology, data management, and artificial intelligence. The programme brings together experimental and computational approaches, guiding participants through the workflow of data-driven biological engineering, currently featured in an ongoing EU research project. Led by experts from Barcelona Supercomputing Center (BSC), University of Ghent (UGent), and Vlaams Instituut voor Biotechnologie (VIB), the summer school combines cutting-edge research with hands-on training across biology, data management, and high-performance computing.

Participants will learn how to extract and curate information from the scientific literature through automated literature scraping and data collection, implement the standardised high-throughput MEMOSA cloning method on automated robotics platforms, and apply best practices in research data management.

The programme includes lectures, interactive sessions, and group work, aiming to provide students and early-career researchers with practical skills and conceptual foundations for integrating synthetic biology with modern data and AI approaches.

With these foundations, participants are introduced to a machine-learning pipeline for analysing and interpreting biological data, highlighting how AI methods can support hypothesis generation and design decisions.

Key information

• The summer school will be three days long (6-8 July 2026) and happening in Ghent, Belgium
• Free of charge 
• Participants are responsible for their own travels and accommodation
• Participation is limited to 20 people
• Open to applicants from diverse backgrounds, however a basic understanding of molecular biology and Jupyter notebooks is  required
• Deadline: 19 June 2026 (midnight, CEST)

Programme overview

Gent University

This workshop provides participants with a comprehensive introduction to microbial production and cloning strategies, starting with a focused class on key concepts and modern methodologies. Participants will then gain hands-on experience assembling production plasmids using the standardized high-throughput MEMOSA cloning method on an automated robotics platform, followed by transformation into E. coli, plating of transformed cells, and verification via colony PCR.
www.ugent.be

Barcelona Supercomputing Center

The workshop introduces students to automated literature mining and data extraction from scientific publications. Working with a real pipeline, students will learn to programmatically retrieve and process large volumes of scientific literature, apply AI and natural language processing to score and rank publications by relevance, and extract structured biological information from unstructured text. By the end of the workshop, participants will have run the full pipeline end-to-end on a substrate of interest, producing a ranked list of candidate substrate-catalyzing enzymes. These skills enable researchers to survey the scientific literature systematically and reproducibly, at a scale that manual curation cannot reach.
www.bsc.es

VIB (the Flanders Institute for Biotechnology)

Unlock the power of FAIR, machine‑readable data. In this hands‑on workshop, you’ll discover why interoperability is essential for making research data truly findable, reproducible, and ready for ML/AI. Through practical exercises, you’ll learn key concepts and approaches to improve reproducibility and future‑proof your research data.
www.vib.be