EUROPIN Summer School on Drug Design – Vienna

September 10 – 15, 2023

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Registration Form

Registration closed!

Thank you for your strong interest. Hope to see you during our next Summer Summer School on Drug Design - 2025.

Instructions for Registration & Payment

Please be sure to follow the instructions below! In the worst case, errors could e.g. result in no ECTS being credited to you or your payment being difficult to trace back to you.

  • Please register to the Summer School on Drug Design 2023 using the respective registration form.
  • If you would like to receive 4 ECTS credits after the Summer School you must also fill out the "Student Enrollment" during registration! Only skip the "Student Enrollment" if you want to attend without ECTS credits!
  • After submitting the registration form, you will receive an email. Be sure to confirm your registration in this email, otherwise it will not be saved!
  • A confirmed registration will then be processed by us. You will receive a personalized invoice after some time. On this invoice you will find further information regarding the payment. It is essential that you follow these payment instructions.
  • Payments by credit card are possible. However, we'll have to forward all your credit card information to the finance department of the University of Vienna, only there credit card payments can be processed. Payment by bank transfer is easier and therefore preferable.

Contact us

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

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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