Tag: teaching

Yurii Aulchenko lecturing at the RSSSO 2014

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Recorded lectures of the RSSSO 2014 now available on YouTube

Back in 2014 we initiated the Research Summer School in Statistical Omics with the help of many friends and colleagues, and with the support (financial and other) from various sources, including the EU-funded MIMOmics project, in which we participate, and the EU-funded Integra-Life project. In a period of two weeks we immersed 13 students (and […]

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https://www.mimomicsucam.com/

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Teaching at the Research MIMOmics Summer School in Cambridge (UK)

From 20 till 27 August, the EU FP7 consortium MIMOmics in which PolyOmica is a partner, organises a Summer School including a Workshop in Omics Studies. The goal of the School is to train a new generation of statistical omics scientists with a biological and biotechnological background to enable them to understand and to apply […]

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Linux commandline

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Case study: The “Linux for scientists” course

Basic Linux command line skills are essential for researchers working in omics science and other fields revolving around big data. In collaboration with the Genetic Epidemiology group of the Erasmus University Medical Centre in Rotterdam, NL, we developed a course called “Linux for scientists” which has been running since 2011. Linux command line skills are […]

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The Erasmus bridge in Rotterdam, NL

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Teaching at the “Advances in GWAS” course in Rotterdam next week

Next week (starting Monday January 30 2017) Yurii and I will be in Rotterdam at the Erasmus University Medical Center where we will teach in the “Advances in Genome-Wide Associations” course of NIHES. This course is part of the Master’s programme in Health Sciences and is compulsory for those who follow the specialisation “Genetic Epidemiology”. […]

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RSSSO2016 group photo

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The 2016 Research Summer School in Statistical Omics

We have just returned from Split, Croatia, where we organised and co-sponsored the third Research School in Statistical Omics (RSSSO2016). With this Summer School we aim to train young researchers (at bachelor, master or PhD level) with a bio{logical,medical,chemical} background and interest in quantitative statistical methods to become the next generation of life scientists; these […]

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