ONLINE EDITION

EUROPIN Summer School on Drug Design – Vienna

September 13 – 17, 2021

Poster Session

Please upload your poster abstract before the deadline by filling out the following form. Deadline for poster abstract submission is July 31, 2021.

By mid August 2021, we will inform you if your poster is accepted or not.

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Please upload your abstract with a maximum of one page in .pdf format.

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The personal information you provide on this page are only used in order to link your abstract with your registration.

Instructions for ECTS Credits

The workload of a univie: summer/winter school is measured in ECTS credits. Use of the ECTS (European Credit Transfer and Accumulation System) at European universities should ensure that it is possible to transfer credits from one university to another (also across borders) and enhance the level of transparency.

Regulations 

Master and PhD students who actively participate during this summer school at the University of Vienna will be credited 4 ECTS. The following criteria have to be fulfilled:

  1. Presenting a poster during the poster session and
  2. writing a 1-page abstract after the summer school about
    • your experiences and achievements accomplished during the Summer School on Drug Design 2021 and
    • how they will impact your research.

Students who do not meet the above mentioned criteria will receive a “Certificate of Attendance” without ECTS credits.


Contact us

If you have any questions regarding the EUROPIN Summer School on Drug Design, please don’t hesitate to contact us at summerschool@europin.at

EUROPIN – a structured, highly interconnected training through research PhD program on the efficient and innovative use of information technologies and computational approaches in the drug discovery, design and development processes.

Organised by

Pharmacoinformatics Research Group 

Following a holistic pharmacoinformatic approach we combine structural modeling of proteins, structure-based drug design, chemometric and in silico chemogenomic methods, statistical modeling and machine learning approaches to develop predictive computational systems for transporters and ion channels.

The validation and optimisation of the obtained in silico models by strong links to experimental groups is an integral part of these activities.

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