Researcher in Advancing Quantum Optimization Techniques for Near-Term Devices Using Hybrid Variational Algorithms - MSCA Postdoctoral Fellowship


  • Job: Investigador/a
  • Department: Multimedia Technologies
  • Location: Barcelona (Spain)
  • Contract: Temporary
  • Working day: Full time
  • Sector: Other
  • Vacancies: 1
  • Discipline: R&D
  • Work modality: Hybrid

EURECAT

Eurecat is the second Research & Technology Organisation in Spain and one of the largest applied research and technology transfer organisation in Southern

Europe. It brings together the experience of more than 800 professionals who generate an annual turnover of 69 million euros and provides services to more than 2,000 companies. Eurecat integrates advanced digital capabilities and experience in biotechnology, industry and sustainability and collaborates with industry in R+D+I activities and projects, offering advanced scientific and technological services and specialized knowledge to respond effectively to the technological needs of very different business sectors, accelerating innovation, reducing both risks and spendings on scientific and technological infrastructures. The technology center participates in more than 200 large national and international consortium projects of high strategic R&I, has 230 patents and 10 spin-offs. Eurecat has eleven centers in Catalonia and presence in Madrid, Malaga and Chile.

Job description

The Quantum Computing Research Group at Eurecat develops advanced quantum software solutions for tackling complex problems in areas such as quantum machine learning and optimization.

They provide access to quantum simulators, hardware, and offer consultancy services to help companies adopt quantum technologies. Their team combines expertise in quantum physics, computer science, and software development. They also collaborate on projects to promote R&D in practical quantum computing applications.

More details can be found here: Quantum computing - Eurecat 

EURECAT Quantum Computing Research Group offers a position for an experienced researcher to develop the following research project Advancing Quantum Optimization Techniques for Near-Term Devices Using Hybrid Variational Algorithms

This position is included in the Ramon Llull-AIRA Postdoctoral Programme and co-funded by the Marie Sklodowska-Curie programme under Horizon Europe. 

Theme Briefing:

Quantum optimization is an emerging field that aims to solve complex optimization problems more efficiently by leveraging the principles of quantum mechanics. Unlike classical optimization methods, quantum optimization uses quantum bits (qubits) to explore multiple potential solutions simultaneously, exploiting phenomena like superposition and entanglement. This approach offers the potential for significant speed-ups in solving problems that are otherwise computationally intractable for classical systems.

The project aims to explore quantum optimization algorithms using variational methods for near-term quantum devices. These devices are anticipated to feature a limited number of physical qubits and low-error correction capabilities, making it essential to leverage hybrid approaches combining quantum and classical resources.
The primary focus will be on applying variational algorithms like the Variational Quantum Eigensolver (VQE) and the Quantum Approximate Optimization Algorithm (QAOA) to both classical optimization problems and problems in quantum chemistry. VQE and QAOA are particularly promising as they use quantum states to represent complex solution spaces, allowing optimization processes that are exponentially hard on classical computers to be tackled more efficiently.
The successful postdoctoral candidate will contribute to advancing these techniques, focusing on developing practical algorithms and validating them on existing GPU clusters and possibly on available quantum hardware.

Available Infrastructures: 34 qubits Quantum Simulator.
Possible Secondments: ICFO, Freie Universität Berlin.
Keywords: Quantum Computing, Quantum Optimization, Variational Algorithms, Quantum Chemistry, Hybrid Algorithms, Error Mitigation.

In order to formalize their application, applicants must complete the registration forms before February 20th, 2025, making sure they provide all the information requested through the link below: 

https://ramonllull-aira.eu/archivos/theme_field/advancing-quantum-optimization-techniques-for-near-term-devices-using-hybrid-variational-algorithms

Guide for Applicants 

https://ramonllull-aira.eu/wp-content/uploads/2024/12/Guide_for_Applicants_RAMON_LLULL_v1.4.pdf

Requirements

Eligibility Criteria: 

  • Researchers must be in possession of a doctoral degree at the deadline of the co-funded programme’s call
  • Candidates must not have resided or carried out their main activity (work, studies, etc.) in Spain for more than 12 months in the three years immediately before the deadline of the co-funded programme’s Open Call.
  • Proficiency in English 

Application Requirements

In order to formalize their application, applicants must complete the registration forms, making sure they provide all the information requested through the link below: 

https://ramonllull-aira.eu/archivos/theme_field/advancing-quantum-optimization-techniques-for-near-term-devices-using-hybrid-variational-algorithms 

adding the following documentation:

  • Curriculum Vitae (CV)
  • Motivation letter
  • Letters of recommendation
  • Digital copy of all academic certificates (Bachelor/Master/PhD). Candidates who have not yet formally been awarded the doctoral degree must include a letter from the doctoral school indicating that the thesis has been submitted and an estimated date for the thesis defence.
  • Research Proposal

Make sure you are including all the required documents checking the Call Documents & Templates section in the programe website Ramon Llull AIRA Open Calls 

 

Job closed

  • Job: Investigador/a
  • Department: Multimedia Technologies
  • Location: Barcelona (Spain)
  • Contract: Temporary
  • Working day: Full time
  • Sector: Other
  • Vacancies: 1
  • Discipline: R&D
  • Work modality: Hybrid