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Research Staff
hace 4 meses
Universidad de Deusto - Investigación
Descripción de la oferta
General call for Grants allocated to research projects or groups to pursue Doctoral Studies in Quantum-Inspired Techniques for Machine Learning and Optimization
Purpose of the position
The domain of quantum inspired approaches has experienced significant expansion, attracting attention from the international research community. As a distinct branch of quantum machine learning and/or optimization models, quantum inspired approaches are dedicated to the creation of classical algorithms that are influenced by quantum mechanics principles yet operate within a traditional computational environment. The intricacies of designing and implementing quantum-inspired models constitute a challenging area of research, with efforts directed towards outperforming traditional algorithmic standards or exploring the distinctive features inherent in quantum-derived models. Contemporary research in quantum-inspired machine learning and optimization is increasingly centered on employing tensor networks. These models leverage an extensive foundation of pre-existing knowledge from classical domains, enriching both the machine learning and optimization disciplines. Moreover, tensor networks maintain an optimal equilibrium between expressive capability and computational efficiency, making them an especially advantageous and intuitive category of quantum circuits. Given the profound theoretical knowledge of their characteristics and the robust algorithms available for their optimization, there is a strong belief that they will offer numerous benefits.
The underlying hypothesis of this research posits that quantum-inspired methodologies, such as tensor networks, can enhance artificial intelligence and machine learning models. The research focuses on enhancing the speed and efficiency of tensor network models, achieving an equilibrium between complexity and effectiveness.
Title of the project to be incorporated
Quantum Lab (DeustoTech) at the University of Deusto.
PI and/or project manager
Iker Pastor y Pablo García Bringas.
Endowment of the contract
Gross salary year 1 of contract: 25.973,10 € Gross salary year 2 of contract: 25.973,10 €Funding Entity
Project: Plan de Impulso de Últimas Tecnologías de Computación Cuántica.
Requisitos
Qualifications required
Qualifications:
Enrolled as PhD student (priority).
Experience required:
Artificial intelligence, physics, quantum computing basics, scientific writing experience.
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 Please complete the following two steps: The 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 «» 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. Curriculum vitae. Letter of admission to a University of Deusto PhD programme or the enrollment in the program.
Application and deadline
+ register at the Deadline: 15th of june 2024 at 23:59 local time Contact information: