Post-Doctoral Position In Quantum Machine Learning And Quantum Artificial Intelligence
The Institute Of Photonic Sciences
Post-doctoral position in quantum machine learning and quantum artificialintelligence
ICFO is offering a postdoctoral position to a well-qualified, highly motivated and dynamic young scientist who wishes to enhance his/her scientific career in a friendly and stimulating environment.
The successful candidate will be joining the Quantum Optics Theory and Quantum Information Theory groups led by Prof. Dr. MaciejLewenstein and Prof. Dr. Antonio Acín , respectively. The groups have experience in all areas of theoretical physics, but in the context of the present project the relevant are: a) classical statistical physics; b) information theory; c) many body physics, including quantum many body physics; d) numerical methods; e) classical and quantum machine learning; f) classical and quantum artificial intelligence. The project will focus on the development of new hardware and software methods to solve optimization problems.
The successful candidate will carry out their tasks within the joint project Quspin (RTC2019-007196-7). Quspin, one of the projects running in the ICFO- Quside Joint Lab, seeks to develop a hardware-accelerated computer system specialized in the efficient and precise solution of some of the most widespread optimization processes. To achieve this goal, we face the challenge from a dual approach: the development and deployment of QuspinAnnealer, an innovative product to accelerate through specialized hardware systems the execution of tempering or annealing algorithms, and the demonstration of its applicability in multiple combinational optimization problems.
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Candidates must hold an internationally-recognized Ph.D.-equivalent degree (or evidence of its completion in the nearest future) preferably in theoretical physics, computer science, applied mathematics.
The candidate should have a proven track record of top-level research during the PhD studies and possible earlier postdoc positions. Positively valued will be experience in the areas a) classical statistical physics; b) information theory; c) many body physics, including quantum many body physics; d) numerical methods; e) classical and quantum machine learning; f) classical and quantum artificial intelligence. Particularly desired is an experience in numerical methods and machine learning.
ICFO is an equal opportunity employer. Candidates are selected exclusively on merit and potential on the basis of submitted application material. No restrictions related to disabilities, citizenship or gender apply to ICFO positions. ICFO abides by the principles of openness, efficiency, transparency, supportiveness, and international comparability as stated in the European Charter for Researchers and the European Code of Conduct for the Recruitment of Researchers.
Salary is offered according to the institutional salary scales.
The contract is offered for periods of one year, renewable for a total of up to 2 years.
Additionally, a family allowance is also available on request and after corresponding approval for people with family charges in the terms described in the corresponding policy.
Suitable candidates are requested to submit:
Presentation letter with a declaration of interest,
Curriculum Vitae, including contact details,
The contact e-mail of two potential referees.
Candidates may contact firstname.lastname@example.org for formal enquiries regarding the application, as well as address scientific enquiries to email@example.com firstname.lastname@example.org
For update information about the hosting group, please visit https: // www. icfo.eu/lang/research/groups/groups-details?groupid=19 and https: // www. icfo.eu/lang/research/groups/groups-details?groupid=23
For updated information about ICFO, please visit https: // www. icfo.eu/
10th of November, 2021