Recent development of modern AI agent systems such as Claude Science, Co-Scientist or Robin presents new opportunities for research. The workshop focused on designing AI agents across various research fields, from methodology (orchestration of agents, benchmarking) to the underlying concepts (ie. knowledge graphs), their implementation on HPC clusters and security of these systems (guardrailing, sandboxing), as well as current options available for researchers at the Charles University. A part of the workshop was dedicated to discussions to share experiences from working with these systems to deepen our understanding and knowledge of them.

The programme included talks by experts in the field from partnered universities of the 4EU+ alliance (Sorbonné Université, University of Warsaw, Heidelberg University), and by experts from the AI interest group.

Location and time:

1.10. - Areál Karlov, Faculty of Mathematics and Physics, Charles University

2.10. - Kampus Hybernská

First day - agenda from 09:00 until 18:30

Second day - agenda from 09:00 until 15:00

The complete agenda, along with presentation information, can be found here.

Workshop Introducing the New Computing Infrastructure at Charles University Faculty of Mathematics and Physics (MFF UK) and the Current Status of the Chimera Cluster. Participants was introduced to the activities of the RSE team, the planned development of computing resources, and opportunities for using AI tools in HPC environments. The program also included a discussion on the future direction of the infrastructure and the needs of the user community.

A lecture within the Foundations of Digital Humanities series at the Faculty of Arts CUNI, focused on the practical use of AI assistants and agent-based systems in programming and software development. The lecture included an introduction to the tools Cursor, Claude Code, and web-based AI coding agents.

This workshop introduces agentic systems in the context of biomedical research and their use in data analysis, workflows, and computational infrastructure.

This one-afternoon course focuses on practical data analysis and visualization in Python using Pandas and Matplotlib.

This two-day introductory course provides a practical foundation in Python programming, designed for beginners and researchers who want to start working with Python for data analysis and scientific tasks. The course is hands-on and practice-oriented, with examples and exercises throughout both afternoons. By the end of the course, participants will be able to write simple Python scripts, process data from files, and perform basic numerical analysis using NumPy.

Online seminar focusing on the introduction of the newly established Research Software Engineering (RSE) team at Charles University and the computational services available to researchers and students.

The workshop focused on developing key skills in automation, efficient data handling, and best practices in research software development.

Participants learned how to automate repetitive tasks using the Unix shell (Bash), work efficiently with files and data via the command line, and gained a basic understanding of version control. They acquired practical experience with Git and the GitHub platform, including tracking changes, reverting to previous versions, and collaborating on software development within a team.