Konferenzen zum Thema Computerphysik und Numerische Simulation in Kanada

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1
5 Day Workshop at BIRS — Biological Active Porous Materials: Modeling, Simulation and Experimentation
04. Okt 2020 - 09. Okt 2020 • Banff, Alberta, Kanada
Zusammenfassung:
One of the key technologies emerging in the 21st century is that of advanced materials, which offer the opportunity to change our lives in many ways, from improving energy efficiency through enabling new biomedical treatments and devices. In order to harness these materials, though, significant progress is needed in developing our understanding of how they work and interact, across scales ranging from those of atoms and molecules through the full size of devices constructed from them. Across the fields of experimentalists, materials scientists, and computational scientists focusing on active biological tissue, significant research is now underway in understanding the properties of both natural and engineered materials across these scales. This workshop brings together experts with distinct views on these materials and devices, aiming to seed the cross-disciplinary research needed to realize their potential to gain new knowledge on active biological materials and to best exploit it. We will bring together a diverse group of world-leading researchers focusing on discussions on the advances currently being made and the collaborations needed to fully unlock the transformative power of advanced materials by using biological active materials as role models.
Eintrags-ID:
1329953
Verwandte Fachgebiete:
2
5 Day Workshop at BIRS — Statistical Modeling for Large Complex Time Dependent Systems
11. Okt 2020 - 16. Okt 2020 • Banff, Alberta, Kanada
Zusammenfassung:
The Banff International Research Station will host the "Statistical Modeling for Large Complex Time Dependent Systems" workshop in the year 2020. This workshop will focus on recent developments and open problems involving the techniques of dimension reduction, dynamic networks, multi-scale modeling for nonlinear processes and count processes, and machine learning, with applications to fields such as climatology, disease mapping, social media behavior, ecology, measurement of small populations, and neuroscience.
Eintrags-ID:
1330029
Verwandte Fachgebiete:
3
5 Day Workshop at BIRS — Multiscale Models for Complex Fluids: Modeling and Analysis
22. Nov 2020 - 27. Nov 2020 • Banff, Alberta, Kanada
Zusammenfassung:
The current workshop is designed to bring together experts in mathematical and numerical analysis as well as mathematical modeling and to create a well-focused environment in which they can discuss recent problems, models and methods developed in their respective fields.
Eintrags-ID:
1330078
Verwandte Fachgebiete:
4
Driving Global Inference for New Physics with Machine Learning, Big Data and Large-scale Statistical Simulation
24. Jan 2021 - 29. Jan 2021 • Banff Centre in Alberta, Kanada
Veranstalter:
Banff International Research Station for Mathematical Innovation and Discovery (BIRS)
Zusammenfassung:
The physical sciences have entered the era of big data, and particle physics is no exception. Extremely powerful particle colliders, telescopes observing light across the energy spectrum, and precise underground experiments have been running for years and have produced remarkably detailed and complex data sets. While no definitive signal of new physics has yet emerged from these experiments, it is quite possible that hints of new phenomena are hidden in these results, only missed due to the limitations of our analysis methods. In this workshop, we will bring together statisticians and physicists to discuss novel methods of data analysis, with a focus on machine learning, in which computers are programmed to think in ways akin to humans. We will launch the development of new computer tools that will allow us to overcome current computational limitations and fully test particle physics theories against all available data, potentially leading to discoveries that will shed light on some of the most profound questions in physics.
Eintrags-ID:
1364042


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Stand vom 07. Juli 2020