2 events found
ELIXIR CZ Artificial Intelligence in Life Sciences I
26 - 27 October 2020
Prague, CzechiaELIXIR CZ Artificial Intelligence in Life Sciences I https://www.elixir-czech.cz/events/elixir-cz-artificial-intelligence-in-life-sciences-oct-2020 https://tess.elixir-europe.org/events/elixir-cz-artificial-intelligence-in-life-sciences-i This workshop will provide a basic introduction to machine learning and its application in Life Sciences, with a special focus on molecular and cell biology. Data-driven approaches penetrate various scientific disciplines, including the fields of biology, biochemistry and biotechnology. Novel technologies of high-throughput data collection and advanced data analysis, such as deep neural networks, offer exceptional opportunities for the development of very complex and accurate mathematical models. The theoretical lectures will cover main methods, algorithms and technologies, illustrate their use in biology and biochemistry research using real-life examples. Hands-on practicals will provide participants with essential skills for the application of machine learning methods and software tools for solving problems in Life Sciences. We plan to continue in our effort to organize follow-ups of this meeting and focus on challenging issues in life science disciplines approachable by AI technology. 2020-10-26 11:00:00 UTC 2020-10-27 14:00:00 UTC ELIXIR CZ, IOCB, FNUSA – ICRC, University of West Bohemia Flemingovo nám. 542, 542, Flemingovo náměstí, Prague, Czechia Flemingovo nám. 542, 542, Flemingovo náměstí Prague Hlavní město Praha Czechia 166 10  https://www.elixir-czech.cz/events/elixir-cz-artificial-intelligence-in-life-sciences-oct-2020   75 workshops_and_courses first_come_first_served Artificial Intelligencemachine learningDrug design
Research Data Management in Life Sciences
9 - 10 November 2020Research Data Management in Life Sciences https://training.vib.be/product/211 https://tess.elixir-europe.org/events/research-data-management-in-life-sciences Upon completion of this course, participants should have an understanding of what Research Data Management is, and why it is important in academic research. They should have an understanding of the FAIR data principles, and how they can make data more FAIR. They should be able to successfully manage all types of research data and to document both the research itself, as well as the data in a comprehensive way. 2020-11-09 09:00:00 UTC 2020-11-10 00:00:00 UTC VIB Bioinformatics Core      publish and share datacreate preservation documentationMigrate data to best mediaMigrate data to best formatcreate user documentationEstablish copyrightcite data sourcesmanage and store datadescribe and document datacapture data with metadataexplore existing data resourcesplan consent for sharingplan data management design research
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