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- ICN2
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. The successful candidate will be joining the Ultracold Quantum Gases group led by Prof. Dr.Leticia Tarruell . The Fermi-Hubbard model is a cornerstone model of condensed matter physics. It describes the physics
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focus on the newly-discovered physical and chemical properties that arise from the behaviour of matter at the nanoscale. ICN2 has been awarded with the Severo Ochoa Center of Excellence distinction
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focus on the newly-discovered physical and chemical properties that arise from the behaviour of matter at the nanoscale. ICN2 has been awarded with the Severo Ochoa Center of Excellence distinction
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institution and they are allocated through recurrent internal calls). Preparation of scientific reports, journal articles and software documentation. Requirements: PhD in Physics, Materials Science, Chemistry
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the composition and function of the microbiome and how the microbiome affects the host. They will be keen to interact with other team members, including PhD students and bioinformaticians, to interchange expertise
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focus on the newly-discovered physical and chemical properties that arise from the behaviour of matter at the nanoscale. ICN2 has been awarded with the Severo Ochoa Center of Excellence distinction
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understanding, capabilities and innovation, while inspiring and providing broad training to the next generations of researchers. Our research lines focus on the newly-discovered physical and chemical properties
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authorship role Education and training A PhD in a relevant field Languages You are proficient in English Technical skills You have advanced MS Office skills Competences Highly developed organizational and
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research lines focus on the newly-discovered physical and chemical properties that arise from the behaviour of matter at the nanoscale. ICN2 has been awarded with the Severo Ochoa Center of Excellence
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physics, which traditionally has relied upon powerful particle colliders, e.g. the LHC at CERN. Axions and axion-like particles (ALPs) are well-motivated dark matter candidates that could solve multiple