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General Information

Aim of the School:

MSFS2021 is an international-short-term school aimed to introduce modeling “from fundamental phenomena up to complex multiphysics environment and multiscale” to fellows involved in research, both in academy and industries, in the field of food and bio processes. Particularly, the school is mainly addressed to fellows involved in research in food and bio-science, technology and engineering, who have limited experiences in modeling and/or fellows with intermediate knowledge who are willing to further improve their modeling skills both in vertical (i.e.: going from simple mono-physics, quite linear problems to multi-physics, non linear problems) and in horizontal direction (i.e.: going from mono-scale modeling to multi-scale modeling).

This year special topic will be “Digitalization in food processing”, exploring the possibilities to adopt digital models and especially digital twins in food processing. Its focus will be how the predictive digital tool can really re-shape the food industry of the (near, already!) future, with the participation of big names of academic and industrial research (as every year). Models are the engines to run digital tools. So knowing how to model and simulate a process and its impact on a food product means holding a tremendous advantage for anybody who wants to be a strong professional in the food industry, to be a leader of innovation. We believe in this.

In the last years, the members of MSFS2021 scientific committee, together with colleagues from all over the World, have built a platform of academic and industrial researchers working about virtualization (modeling – from multiscale to multiphysics, simulation, optimization, etc) in food and bio sector and sharing the vision that modeling and simulation are today under-represented in food and bio processing, compared with the advantages that this approach has brought in other technological sectors.

 

A maximum number of 20 participants will be selected on the base of their CV and motivation. Priority will be given to PhD students, Post-Doc and Researchers involved in industrial R&D.

 

 

 

 

Email

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