We’re excited to announce that we’re having a summer school this July!
“Hands-on summer school: Fundamentals in integrating synthetic biology, data, AI” is a three-day summer school from 6-8 July 2026, designed to introduce participants to the emerging intersection of synthetic biology, data science, and artificial intelligence through practical, hands-on training.
Participants will learn how to extract and curate information from the scientific literature through automated literature scraping and data collection (with our partners from BSC), implement standardised experimental design using the standard assembly line framework (with the UGENT team), and apply best practices in research data management (together with VIB).
The program 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. In short, it combines experimental and computational approaches and guides participants through the workflow of data-driven biological engineering.
Due to space and resource constraints, attendance will be limited to 20 participants, and the summer school will take place in Ghent.
Apply here: https://ec.europa.eu/eusurvey/runner/summerschool-registration2026
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.
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.
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
Recent Comments