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Description of the offer : The condensed matter theory group at Institut Néel (CNRS, Grenoble) invites applications for a three-year PhD position in condensed matter physics starting from October
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-intensive PhD training programme, supported by the PRIDE funding scheme of the Luxembourg National Research Fund (FNR) and the programme's partner institutions: University of Luxembourg, Luxembourg Institute
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SPINTEC fabrication facilities. As such, this thesis will be stationed mostly at SPINTEC in Grenoble, the PhD program being registered at Université Grenoble Alpes. You will also be part of the Vertical
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, public authorities in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? We are seeking a PhD
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Description of the offer : The main objective of this PhD thesis is to unravel the microscopic mechanisms by which the hydrogen affects the properties of intermetallic magnets. To achieve this goal
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observed in Drosophila larvae. This interdisciplinary project combines biology, neuroscience, and computational modelling to understand how the larva’s body’s physical properties influence its motor control
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Description of the offer : Spin triangles are magnetic molecules predicted to display spin chirality, magnetoelectricity and protected quantum degrees of freedom. These characteristics could allow electric spin control and long spin coherence properties. In the past we have confirmed the...
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of Europe in the 20th and 21st centuries. It serves as a catalyst for innovative and creative scholarship and new forms of public dissemination. Your role Conduct a PhD Thesis Contribute to our dedicated
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PhD grant proposal - Carcinogenesis study tools for bioTechnologies and medicine of the future H/F PhD grant proposal : HYMPACT: Modular HYdrogels mimicking the healthy and pathological PAncreatic
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exciting opportunities for machine learning to address outstanding biological questions. The PhD student to be recruited will be working on the development of machine learning methods for single-cell data