Casimir Course - Machine Learning for Quantum Experiments



10:00-17:00hrs (3-day block course)


Delft: C1.190 (Building 58, van der Maasweg 9) on Wed-Thur; and Room 0.96 (Building 23, Stevinweg 1) on Friday


Update October 3rd: we've reached our maximum capacity of participants. You can still register for the waiting list (see form below), but your participation depends on cancellation of others.

Machine learning methods have proven to be powerful tools for complex data processing tasks across a range of disciplines. Quantum technologies and quantum computing have not been an exception and first experiments that have been controlled, or analyzed by AI have been conducted. Following the interest of PhD students, we have created a PhD course that will discuss applications of machine learning techniques for control and analysis of quantum devices.

This 3-day block course consists of 3 lectures (10:00-12:00h) and 6 hands-on sessions (13:00-15:00h and 15:30-17:30h). For the subjects covered in these sessions, please download the course schedule below.

Instructors: Eli┼íka Greplová (PI/QN), Guliuxin Jin (PhD/QN), Arash Ahmadi (PhD/QN), and Vinicius Fonseca Hernandes (PhD/QN).

Audience: This course is mainly intended for PhD students of the Casimir Research School. Postdocs and motivated master students are welcome too.

Prerequisites and equipment: Students will use their own laptops and work in Jupyter Notebooks in Google Collaboratory, no special software or equipment besides laptop is required. The participants of the course should have at least rudimentary knowledge of programming in Python, and basic knowledge of quantum physics or quantum computing. Previous knowledge of machine learning is not needed.

Dates and venues: Course dates are October 26-28th, every day from 10:00hrs until 17:00hrs. On Wednesday and Thursday, the course will take place in Room C1.190, Building 58 (TNW, van der Maasweg 9, Delft), and on Friday in Room 0.96, Building 23 (CiTG, Stevinweg 1, Delft).

Credits: Those participants who attended the complete course (all three days) will be awarded 3 Graduate School Credits (GSCs).

Registration [CLOSED]
You can register for the course' waiting list by filling in the form below. Since seats are limited - and we've reached our maximum capacity of 50 participants - you're participant depends on cancellation of other participants.

The data we collect are used for organizational purposes only and won't be stored longer than absolutely necessary. For more details, see our privacy statement.


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