Tensor Networks for Quantum Machine Learning Variational Algorithm Simulation (QMLVA simulation) in application to Artificial Vision: This position focuses on exploring the use of Tensor Networks (TN) as an efficient tool to simulate Quantum Variational Algorithms (QVA) in the context of Quantum Machine Learning (QML).
Given the significant limitations of current quantum hardware, such as noise and restricted availability, the project aims to optimize simulation techniques using TN, comparing their effectiveness against classical machine learning algorithms and QML implemented on quantum hardware.
This will help identify optimal TN configurations, assess their generalization and scalability capabilities, and provide practical guidance on selecting the most suitable technology based on the problem and available resources.
It is being explored the application to AV.
Title of the project to be incorporated: Quantum Lab (DeustoTech) at the University of Deusto PI and/or project manager: Endowment of the contract: 27.262,05 €/year.
2 years Funding Entity: Requirements Qualifications: Master or qualification to enroll as PhD student.
Experience required: To successfully execute this proposal, advanced expertise in quantum computing is required, with a strong understanding of quantum algorithms, particularly Variational Quantum Algorithms (QVA) and Quantum Machine Learning (QML).
A solid foundation in mathematical concepts related to Tensor Networks (TN) and their application in simulating quantum systems is essential, along with proficiency in programming and the use of specialized tools and libraries such as TensorFlow, TeNPy, Qiskit, or Pennylane.
Additionally, strong research and analytical skills are needed to conduct comprehensive state-of-the-art reviews, as well as experimentation and optimization capabilities to compare configurations and evaluate performance in terms of scalability, accuracy, and efficiency.
Experience with advanced hardware, including quantum simulators and high-performance computing systems, is critical, alongside expertise in technical report writing and effectively communicating results to the scientific community.
Application The University of Deusto carries out this call within the framework of "General call for Grants allocated to research projects or groups to pursue Doctoral Studies." For more information on this call, please click on the following link.
Please complete the following two steps: Register at the Deusto Career opportunities website (click on the blue "register" button).
Official academic transcript of previous official university studies (1st and 2nd cycle), even if they are currently being taken, issued by the corresponding unit.
The academic certificate must state the name of the degree programme, the subjects that make up the course syllabus, the subjects passed, the grades obtained and the dates on which they were obtained.
The transcript should show the average mark from 0 to 10.
If the studies have been completed abroad, an official academic certificate must be submitted as well as a sworn translation thereof, provided that it is not in one of the two co-official languages of the Basque Autonomous Community or in English.
In all cases, the certificate or other supporting document must state the maximum and minimum grades within the corresponding assessment system and the minimum grade required to pass.
In addition, the «Statement of equivalence of average grade» of the Spanish Ministry of Education, Culture and Sport (MECD) or ANECA's official certificate indicating the average grade of the academic transcript within the Spanish evaluation system must be submitted.
Letter of admission to a University of Deusto PhD programme or the enrollment in the program.
Deadline: January 2th 2025 23:59 local time.
#J-18808-Ljbffr