Welcome to the eSSENCE-SeRC multiscale modelling meeting 12-14 June 2017!
Multiscale Modelling of Materials and Molecules 2017 will take place at Uppsala University from 12th to 14th of June, at the Biomedical center (BMC) located in the BMC-Ångström-ITC campus area. Among the topics that will be covered are:
* Data-driven or physics-driven models? * Modelling as a characterization tool. * Molecular dynamics simulations and sampling techniques. * From electronic calculations … *… to atomistic (force-field) models … *… to more coarse-grained simulations * Along the multiscale ladder. * Accuracy and validation. All e-science actors (“modellers”) and interested colleagues are warmly invited to participate and contribute!
The eSSENCE meeting is free of charge, including all meals.
Registration is open! The deadline for registration and abstracts submission is 17 May 2017.
The international key-note speakers include:
- Dr. James A. Warren (Director, Materials Genome Program, NIST, USA)
“Materials informatics and the US Materials Genome Initiative“
- Dr. Erich Wimmer (Chief Scientific Officer, Materials Design S.A.R.L, France)
“Data and materials discovery: Perspectives from a Software Company“
… MATERIALS …
- Professor Seungwu Han (Seoul National University, South Korea)
“Interface research at the interface between fundamentals and industry:
Organic electronics and energy materials“
eSSENCE research in focus
Large-scale analysis of live cells
Obtaining quantitative data from large-scale experiments of live cells is of great importance for understanding molecular and cellular processes such as basic cellular processes in bacterial cells, and for design of personalized treatments based on cancer stem cells from patients. Live-cell experiments carried out using automated imaging systems often produce massive amounts of data containing far more information than can be digested by a human observer. A recurring task in many experiments is the tracking of large numbers of cells or particles and the analysis of their spatiotemporal behavior. The importance of using computer vision-based methods to accomplish this task is well recognized, but in practice investigators often encounter obstacles due to the lack of user-friendly software and infrastructure in terms computing resources and data storage.