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CANMOD – Training
Method
1
#701011
We are building expertise amongst the next generation of infectious disease modellers, and preparing them for careers in academia, industry, and the public sector.
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EIDM »
EIDM
EIDM ☜The Emerging Infectious Diseases Modelling Initiative (EIDM) – by the Public Health Agency of Canada and NSERC – aims to establish multi-disciplinary network(s) of specialists across the country in modelling infectious diseases to be applied to public needs associated with emerging infectious diseases and pandemics such as COVID-19. [1]☜F1CEB7
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Networks »
Networks
Networks☜Learn more about the five EIDM networks: CANMOD, MfPH, OMNI, OSN, and SMMEID.☜79B9B9
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CANMOD »
CANMOD
CANMOD ☜CANadian Network for MODelling infectious Disease / Réseau CANadien de MODélisation des maladies infectieuses☜79B9B9
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CANMOD – Training
CANMOD – Training☜We are building expertise amongst the next generation of infectious disease modellers, and preparing them for careers in academia, industry, and the public sector.☜AECCD8
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2022/03/03 Technique in Biostatistics and Epidemiology »
2022/03/03 Technique in Biostatistics and Epidemiology
2022/03/03 Technique in Biostatistics and Epidemiology☜Module 1: Applied probabilistic programming – Probabilistic programming provides a flexible and automatic implementation of efficient procedures for Bayesian statistical analysis. This module will provide a general background on the Hamiltonian Monte Carlo sampler, which underlies the popular Stan programming language, followed by a practical demonstration of Stan in R.☜E883B6
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22/03/28 COVID-19 Model Comparison Workshop »
22/03/28 COVID-19 Model Comparison Workshop
22/03/28 COVID-19 Model Comparison Workshop☜To compare models, identify key unknown parameters, and determine how much they affect key outcomes.☜E883B6
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22/08/02 Compositional methods for health modeling »
22/08/02 Compositional methods for health modeling
22/08/02 Compositional methods for health modeling☜The intended audience is mathematical epidemiologists and dynamic modelers for infectious diseases, health and health care seeking to learn about emerging methods and tools, based on applied category theory, for constructing large-scale models efficiently, reliably, and modularly. [1]☜E883B6
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23/08/14 Taming the BEAST workshop »
23/08/14 Taming the BEAST workshop
23/08/14 Taming the BEAST workshop☜Bayesian Evolutionary Analysis by Sampling Trees: Taming the BEAST – August 14 to 18, 2023, Howe Sound Inn & Brewing, Squamish, British Columbia. BEAST 2 is an open source cross-platform software package for analysing genetic sequences in a Bayesian phylogenetic framework. Participants will be equipped with the skills and core knowledge to confidently perform and interpret inference generated from phylogenetic and phylodynamic analyses.☜E883B6
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23/08/19 AARMS-EIDM Summer School on Modelling Infectious Diseases »
23/08/19 AARMS-EIDM Summer School on Modelling Infectious Diseases
23/08/19 AARMS-EIDM Summer School on Modelling Infectious Diseases☜Organizer: Dr. A. Hurford, Dates: August 19-31, 2023, Venue: Bonne Bay Aquarium and Research Station (BBARS), Newfoundland and Labrador (NL).The AARMS-EIDM Short Summer School on Modelling Infectious Diseases aims to fulfil a deliverable listed in the Atlantic Association for Research in the Mathematical Sciences (AARMS) support letter for 3 networks in the Emerging Infectious Disease Modelling Initiative (EIDM) Consortium: to run an AARMS summer school.☜E883B6
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23/11/12 CANMOD: Progress and Next Steps »
23/11/12 CANMOD: Progress and Next Steps
23/11/12 CANMOD: Progress and Next Steps☜The Banff International Research Station will host the The Canadian Network for Modelling Infectious Diseases: Progress and Next Steps workshop in Banff from November 12 to November 17, 2023. Organizers: David Earn (McMaster University), Caroline Colijn (Simon Fraser University), Irena Papst (Public Health Agency of Canada).☜E883B6
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Job opportunities »
Job opportunities
Job opportunities☜☜55C38A
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Training »
Training
Training☜☜FFFACD
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Entrée par:
David Price
NodeID:
#701011
Node type:
Method
Date d'entrée (GMT):
9/16/2022 10:20:00 AM
Date de la dernière modification (Heure GMT):
8/23/2023 8:31:00 AM
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