Leading university:
Charles University, Faculty of Science
Project leader:
Felipe Martínez-Ramírez
Participating universities:
Charles University, Heidelberg University, University of Copenhagen, University of Milan, University of Warsaw, Czech Technical University in Prague (ČVUT)
The "AI-Enhanced Mass Spectrometry (MS) Processing and Presentation" project aims to leverage machine learning and AI tools to enhance the application of mass spectrometry in scientific research and presentations. With the increasing complexity of MS-based data, there is a pressing need for specialized training in computational methods to efficiently process and interpret this data. This initiative will host a three-day workshop providing hands-on training with various computational tools essential for MS-based metabolomics and data processing using AI.
The workshop is designed to cater to all levels of expertise, particularly beginners, and will include a crash course on using AI in scientific writing to present MS-based data. Experienced lecturers, including software developers and seasoned users of both open-source and licensed programs, will guide participants through the practical application of AI software in data processing and interpretation of metabolomics. Selected students will have the opportunity to present their AI-related MS projects. The event aims to foster an environment of learning and collaboration among attendees, promoting the exchange of ideas and experiences, and paving the way for future collaborations across the 4EU+ Alliance members.
Application deadline: 16 August 2024