Casimir Course - Machine Learning for Quantum Experiments - registration open



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


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).

You can register for the course by filling in the form below. Please note that seats are limited - we can accept 50 participants. Your place at the course will be confirmed via email after registration is closed and participants have been selected (most likely the end of September).

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