3rd Annual Summer School “Machine Learning for Personalized Medicine”
21 September 2015 - 25 September 2015
United Kingdom
The countdown has started! We will meet in 2.5 weeks in Manchester, UK at the historical site of the Museum of Science and Industry (MOSI). The Programme has now been published on our website mlpm.eu.
There is still time to register and to join us for 5 interesting days full of lectures, discussions and opportunities to meet international scientist/students and to establish contacts and networks.
Registration deadline is Thursday next week (September 10).
For registration please click here:
http://onlineshop.shef.ac.uk/browse/extra_info.asp?compid=1&modid=2&deptid=7&catid=106&prodid=426(opens in new window)
In order to book the event you will need to register at the Sheffield Online Store first. For booking the event, please choose Category 4 (requires this password: MLPMSS2015).
MLPM is a Marie Curie Initial Training Network, funded by the European Union within the 7th Framework Programme. MLPM started on January 1, 2013 and is a consortium of several universities, research institutions and companies located in Spain, France, Germany, Belgium, UK, Switzerland, Israel and in the USA. MLPM involves the predoctoral training of 14 young scientists in the research field at the interface of Machine Learning and Medicine. Its goal is to educate interdisciplinary experts who will develop and employ the computational and statistical tools that are necessary to enable personalized medical treatment of patients according to their genetic and molecular properties and who are aware of the scientific, clinical and industrial implications of this research.
The field of machine learning, which tries to detect patterns, rules and statistical dependencies in large datasets, has also witnessed dramatic progress over the last decade and has had a profound impact on the Internet. Amongst others, advanced methods for high-dimensional feature selection, causality inference, and data integration have been developed or are topics of current research. These techniques address many of the key methodological challenges that personalized medicine faces today and keep it from rising to the next level. Despite this rich potential of machine learning in personalized medicine, its impact on data-driven medicine remains low, due to a lack of experts with knowledge in both machine learning and in statistical genetics. Our ITN aims to close this gap by bringing together leading European research institutes in Machine Learning and Statistical Genetics, both from the private and public sector, to train 14 early stage researchers.
There is still time to register and to join us for 5 interesting days full of lectures, discussions and opportunities to meet international scientist/students and to establish contacts and networks.
Registration deadline is Thursday next week (September 10).
For registration please click here:
http://onlineshop.shef.ac.uk/browse/extra_info.asp?compid=1&modid=2&deptid=7&catid=106&prodid=426(opens in new window)
In order to book the event you will need to register at the Sheffield Online Store first. For booking the event, please choose Category 4 (requires this password: MLPMSS2015).
MLPM is a Marie Curie Initial Training Network, funded by the European Union within the 7th Framework Programme. MLPM started on January 1, 2013 and is a consortium of several universities, research institutions and companies located in Spain, France, Germany, Belgium, UK, Switzerland, Israel and in the USA. MLPM involves the predoctoral training of 14 young scientists in the research field at the interface of Machine Learning and Medicine. Its goal is to educate interdisciplinary experts who will develop and employ the computational and statistical tools that are necessary to enable personalized medical treatment of patients according to their genetic and molecular properties and who are aware of the scientific, clinical and industrial implications of this research.
The field of machine learning, which tries to detect patterns, rules and statistical dependencies in large datasets, has also witnessed dramatic progress over the last decade and has had a profound impact on the Internet. Amongst others, advanced methods for high-dimensional feature selection, causality inference, and data integration have been developed or are topics of current research. These techniques address many of the key methodological challenges that personalized medicine faces today and keep it from rising to the next level. Despite this rich potential of machine learning in personalized medicine, its impact on data-driven medicine remains low, due to a lack of experts with knowledge in both machine learning and in statistical genetics. Our ITN aims to close this gap by bringing together leading European research institutes in Machine Learning and Statistical Genetics, both from the private and public sector, to train 14 early stage researchers.
Keywords
Bioinformatics, Biostatistics, Big Data, Machine Learning, Personalized Medicine