QML-CVC group – Quantum Machiine Learning

The Quantum Machine Learning Group at CVC

People

The QML-CVC group is a multi-disciplinary team comprised of physicists, computer scientists, experts in computer vision, machine learning and quantum information. Know more about every one of us by clicking above.

Research

Our research tackles the bridge between the Q (quantum information) and the ML (machine learning) fields of knowledge, from both a basic and oriented perspective. Our aim is to provide a roadmap for quantum computing in the field of computer vision.

Lattest webinar at QML-CVC

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OPEN POSITONS AVAILABLE AT QML-CVC. More infor HERE

ML-QSIM: 4-year 2M€ project awarded in collaboration with CSIC’s Rydberg quantum simulator team

The QML.CVC will participate in the the project “Machine Learning for Quantum Simulations with Rydberg Atoms (ML-QSIM)”, in collaboration with SCIC institutions CINN, INMA and ICMM. The roie of the QML-CVC group will be to develop explorative research pathways in computer vision through quantum machine learning . The grant is funded by the Spanish Ministry of Science, Innovation and Universities. During the following 4 years, this will allow for the QML-CVC group to consolidate new PHDs and POSTDOCS, while advancing QML knowledge in the context of one of the strategic infrastructures of the Spanish Quantum Agenda.

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OPEN POSITION:
3-YEAR POSTDOCTORAL CONTRACT (AIRA)

The QML-CVC group is offereing a 3-year FULL TIME POSTDOCTORAL CONTRACT within the The Ramon Llull-AIRA Postdoctoral Programme, co-funded by the Marie Sklodowska-Curie programme under Horizon Europe.

Applications open until 20th Februrary 2025

Call open (expected): 20th December 2025
Application deadline (Expected): February 20, 2026, at 24:00 CEST.
Evaluation and Selection period: March – June 2026.
Results announced: July 2026.
Fellowship start date: September – December 2026 (flexible start).

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OPEN POSITION:
PhD IN QML (PHYNEST)

The QML-CVC group is offereing a FULLY GRANTED 4-year PhD Position in Quantum Machine Learning in the context of the PHYNEST PhD Programme, co-funded by the Marie Sklodowska-Curie programme under Horizon Europe.