Daniele Cucurachi

MS Thesis at Cambridge | Physics MSc Student at EPFL | Vice President EPFL QC Association

About Daniele

Physics master’s student at EPFL with a passion for modern technologies and their innovative applications in industry. Ex Quantum Engineer at IQM Quantum Computers, currently working on my master’s thesis at University of Cambridge and Vice President of the EPFL Quantum Computing Association.


  • ANSYS HFSS (High Frequency Simulation Software)
  • GitLab, GitHub with Git for version control (collaborative programming)
  • KLayout
  • LaTex
  • LTspice
  • Machine learning
  • Microsoft Office
  • Python (Qiskit, KQCircuits, QuTip, PyTorch, Scikit-Learn, Gdspy)

Work Experience

Feb 2022 - Sept 2022
Quantum Engineer
IQM Quantum Computers
Worked on the development of Python libraries for automating the design and simulation of superconducting quantum circuits (https://github.com/iqm-finland/KQCircuits and other IQM's private software projects)
Jan 2021 - Present
Vice President
EPFL Quantum Computing Association
• Managed Communications & Events team (6 people) • Obtained sponsorship from the companies "Quantum Machines" and "McKinsey & Company" • Participated in the organization of quantum computing related events which involved both academia and industry, the last one being EPFL QCA Quantum Hackathon: more than 80 international participants, event focused on quantum chemistry simulation
Sep 2021 - Jan 2022
Research Intern
Hybrid Quantum Circuit Lab (EPFL)
Design optimization of a waveguide in the microwave domain based on an architecture of periodic arrays of coupled resonators to obtain flat transmission across a defined frequency range through apodization and study slow light applications. The project involved computer simulations (Sonnet Software and ANSYS HFSS) and the development of a Python library to optimize and speed up the design process of the devices.

Education & Training

Sept 2022 - March 2023
Master's Thesis
University of Cambridge
Visiting student at Cambridge working with the Quantum Information Group (https://www.qi.phy.cam.ac.uk/) on efficient quantum circuits for chemistry simulations.
2020 - 2022
Master's Degree in Physics
EPFL (École polytechnique fédérale de Lausanne)
GPA: 5.6/6 Courses: • Machine Learning • Artificial Neural Networks • Quantum Computing and Quantum Information (Quantum Algorithms) • Quantum Optics and Quantum Information • Quantum Physics III (Advanced Quantum Physics) • Quantum Transport in Mesoscopic Systems • Solid State Systems for Quantum Information Processing • Semiconductor Physics and Light-Matter Interaction • Physics of Photonic Semiconductor Devices • Frontiers in Nanoscience (Nanostructures Fabrication and Characterization) • TEM (Transmission Electron Microscopy) Advanced Methods • Experimental Methods in Physics
2017 - 2020
Bachelor's Degree in Physics Engineering
Politecnico di Torino
• Graduated with: 110 with honours / 110 (top grade) • Several team projects in the field of applied physics (photonics and measurements in cryogenic environment) and electronics (electronic measurements, basic circuits design and simulation)
United Kingdom