Join us for a hacking experience at the AI4Life Hackathon, where computational experts will collaborate to enhance the user experience of the BioImage Model Zoo.Kickstarting the week, participants will introduce […]
Artificial intelligence (AI) is transforming virtually all areas of science, and the life sciences are no exception. AI-based methods are pushing the limits of what is possible in experiment design, […]
This virtual course will show how public bioimaging data resources, centred around the BioImage Archive, enable and enhance machine learning based image analysis. The content will explore a variety of […]
AI4Life experts will work together to ensure that the infrastructure and services provided by AI4Life are in line with the needs of the projects selected at the Open Calls and Challenges.
EMBO Practical Course on Deep learning for microscopy image analysis at Human Technopole in Milan (Italy). The goal of this course is to familiarize researchers working in the life sciences […]
Join us at Universidad Carlos III de Madrid from June 10-14 for a dynamic Workshop & Hackathon/Uploathon hosted by AI4Life. This event focuses on leveraging zero-code tools for AI-driven microscopy […]
The pre-symposium Workshop & Hackathon will be held on August 26th-27th, 2024, at the Institute Gulbenkian de Ciência (IGC) in Oeiras, Portugal and will be co-hosted by AI4Life. The event will be focused on […]
This AI4Life Hackathon focuses on advancing the core functionality and long-term sustainability of the BioImage Model Zoo and ecosystem. This 4-day event brings together a diverse group of scientists and […]
The AI4Life Annual Meeting and General Assembly brings together the AI4Life project partners at the Human Technopole in Milano on October 21st-22nd, 2024. All AI4Life partner institutions as well as all […]
The 2024 I2K conference, happening October 23-25 at the Human Technopole in Milan, Italy, is a key meeting point for anyone passionate about the intersection of life sciences and quantitative image analysis.
This virtual course will show how public bioimaging data resources, centred around the BioImage Archive, enable and enhance machine learning based image analysis. The content will explore a variety of […]