Enhance productivity and creativity with generative AI tools
From February 26th to 27th, 2026 the Cell-ID research program invites researchers to gather at the Institut Curie to dive into Generative AI tools.
GenAI tools, especially Large Language Models like ChatGPT and Copilot are transforming the way we work, communicate, and manage research. This course introduces participants to the practical use of these tools to streamline workflows, enhance creativity, and solve real problems efficiently.
The event will take place in two parts : part 1 is open to everyone, part 2 has limited seating and priority is given to Cell-ID members. Please register for Part 2 and we will let you know if you have been selected.
Part 1 – Introduction to Generative AI and Prompt Engineering (4h – Open to everyone)
Discover the foundations of Generative AI and Large Language Models, learn the principles of effective prompting, and get insights into real world examples of how these tools can simplify daily research and management tasks.
Part 2 – Hands-on Workshop: Creative Problem-solving with GenAI (8h – registration open until January 30th, priority is given to Cell-ID members)
Apply your knowledge to real-life challenges through guided group activities. Learn to define problems, test AI-assisted solutions, and design automated workflows and AI agents that combine human insight and AI capabilities to boost innovation and efficiency.
About the trainers you will meet:
Jonas Krebs, PhD
| Jonas Krebs has spent over 15 years navigating the intersection of science and science management, looking for creative and smarter ways to manage complex research environments. As Coordinator of Strategic Projects at the Centre for Genomic Regulation (CRG) in Barcelona, he supervises a team of Scientific Project Managers, helping to turn ambitious ideas into reality by optimizing workflows, securing funding, and integrating emerging technologies into daily operations. With a PhD in Molecular Biology and two research management certifications (PMP, EU Liaison Officer Research), Jonas has a deep understanding of both the scientific and operational sides of research. Lately, his focus has turned to the transformative potential of GenAI as a practical tool that can revolutionize the way researchers, administrators, and project managers work. He has been actively experimenting with AI-driven automation, workflow optimization and searching for impactful and user-friendly applications of LLMs. Jonas is also a co-founder and former chair of the Research Management Working Group within the Marie Curie Alumni Association (MCAA), a community of over 250 professionals across Europe dedicated to improving research management on an international scale. |
David Brena, PhD
| David is a scientist turned scientific project manager and digital tools enthusiast with a keen interest in improving research management through technology. With a background in Biotechnology Engineering (B.A.Sc., Monterrey Institute of Technology, Mexico) and Biomedicine (M.Sc., Ph.D., University of Barcelona), he has worked in disease modeling, gene editing, epigenetics, and oncology. Drawing on his engineering mindset, scientific curiosity, and project management experience, David specializes in strategic international research projects’ full life cycle, ranging from the research idea, proposal writing, consortium management, and general implementation. Passionate about digital transformation, he actively incorporates Generative AI and other emerging tools into research management workflows, aiming to simplify daily tasks and enhance efficiency. |
Daniel Scavello, MSc
| Daniel Scavello is an emerging scientific project manager with a background in Biochemistry (BSc, Universitat Autònoma de Barcelona) and a Master’s in Health and Science Management (MSc, Universitat Autònoma de Barcelona). His deep passion for science and strong interest in research management have driven his transition into this field, where he explores ways to enhance research administration through technology and innovation. Building on his scientific background and project management experience, Daniel is particularly interested in how Artificial Intelligence and digital tools can streamline research administration, foster collaboration, and improve operational efficiency. He actively seeks strategies to automate processes, optimize data management, and implement seamless workflows that reduce administrative burdens and enhance research management effectiveness. |