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Multiscale and hybrid algorithms for stochastic chemical kinetics

Posted on April 18, 2012January 15, 2013 By admin No Comments on Multiscale and hybrid algorithms for stochastic chemical kinetics

Many biochemical network models display scale separation with respect to reaction rates and/or molecular copy numbers. Depending on the type of question under study, different models are best suited to simulate the system. For some parts of the system, a macroscopic model might be appropriate. For other parts, a mesoscopic model may provide additional insight into the models dynamics. In other cases, a microscopic model might be needed to capture the fine-grained features of the model. To efficiently simulate systems that have different requirements with respect to modeling levels, hybrid methods offer an attractive approach.

Multiscale methods, Reaction Diffusion Master Equation, Stochastic Chemical Kinetics

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Data-and simulation-driven life science. Much of our work in eScience and applied ML has applications in life science, and in Systems Biology in particular. We aim to enable data-and simulation-driven scientific discovery.

HASTE - a cloud native framework for intelligent processing of image streams: http://haste.research.it.uu.se/

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Join our great team at @SciLifeLab_DC!

We are now looking for IT-ansvarig SciLifeLab
👉Apply by Dec 12th.
👉More & apply here: https://www.kth.se/om/work-at-kth/lediga-jobb/what:job/jobID:546469/where:4/
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Starting in 30mins :-)

Prashant Singh@prashant_rsingh

Join us tomorrow for an exciting seminar by @uPicchini on “guided sequential ABC schemes for intractable Bayesian models”. The seminar starts at 13.15 until 14.00 CEST in Room 101127, Ångströmlaboratoriet, Uppsala University & online: https://uu-se.zoom.us/j/65354024469. Warmly welcome!

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6 Oct

eSSENCE, SERC and Chalmers e-science Centre are providing core e-science education to PhD students from the SeSE platform: https://sese.nu/

Researchers - get funding to develop and give a PhD course!
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Day two of the Swedish eScience Academy organized by eSSENCE.

Interesting to learn from Sverker Holmgren of Chalmers eCommons about the holistic approach to infrastructure and support for data centric research at Chalmers!

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So great to be at the Swedish e-science Academy organized by #essenceofescience! Two days of scientific exchange between colleagues nationally, and in particular from the partner universities @UU_University @UmeaUniversity @lunduniversity.

Keynote day one by Kersti Hermansson.

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Decentralized AI, Federated Learning. One focus area of the group is development of methods and software to address decentralized and privacy-preserving AI. We are core contributors to the FEDn open source framework for scalable federated machine learning:

https://github.com/scaleoutsystems/fedn
Introduction to Federated Learning by Andreas Hellander
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Scaleout Systems is a spin-out from ISCL on a mission to enable decentralized AI and federated learning to production.

https://www.scaleoutsystems.com/

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