AI for Life Sciences and Agri-Food Research

About

The Summer School explores the application of Artificial Intelligence in Life Sciences and Agri-Food, integrating biology, agronomy, and data science to enhance research and experimentation.
Participants will gain practical knowledge of machine learning, deep learning, meta-analysis, experimental design, and data agents, acquiring the tools to optimize workflows, interpret complex data, and communicate scientific results effectively.
A central aspect of the course will be the development of data interpretation and modelling skills, enabling participants to integrate different sources of information to gain a deeper understanding of biological and production systems, as well as to support the writing of scientific articles. The programme will promote the interaction between young researchers and experienced scientists in the field, creating an environment for discussion and collaboration that will stimulate new ideas and innovative research approaches

Target group

PhD students, Postdoctoral researchers, Master’s students.

Course aim

The Summer School provides advanced training in the application of Artificial Intelligence to biological and agro-food research, combining theory and hands-on activities on machine learning, deep learning, omics, and environmental big data analysis, AI agents for experimental design and data interpretation, with a strong focus on reproducibility, data integrity, and ethical implications of AI in science

Fee info