Universität Wien
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260082 VU Quantum Machine Learning for Computational Materials Design (2021W)

5.00 ECTS (3.00 SWS), SPL 26 - Physik
Continuous assessment of course work
ON-SITE

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 15 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

This course will take place on the dates and at the locations indicated above.

  • Thursday 07.10. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 14.10. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 21.10. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 28.10. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 04.11. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 11.11. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 18.11. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 25.11. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 02.12. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 09.12. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 16.12. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 13.01. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02
  • Thursday 20.01. 08:00 - 10:30 Seminarraum 18 Kolingasse 14-16, OG02

Information

Aims, contents and method of the course

The typical outline is
-Introduction
-Quantum mechanics in chemical compound space
-Machine learning in chemical compound space
-High-Performance Computing
-Examples

Assessment and permitted materials

Graded homework assignments

Minimum requirements and assessment criteria

This is an advanced, research oriented course (Master and PhD students typically attend) which I've been developing over the last couple of years. It closely follows the research domain where my lab is actively contributing. Prerequisites include experience with:
-programming
-quantum mechanics
-applied math
-atomistic simulation

Examination topics

Topics covered in the course.

Reading list

Review articles written by author and other peers in the field.

Association in the course directory

M-VAF A 2, M-VAF B

Last modified: We 06.10.2021 21:29