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Grenoble Alpes (UGA) and the ESRF enabling the partners to combine their complementary expertise to deliver pioneering, high-impact research on these novel functional materials. The PhD student will benefit
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Organizing meetings and workshops to promote awareness and advocacy Your profile Master's degree (or soon-to-obtain) in Psychology, Cognitive Science, or Education A track record of interest in technology
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Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices
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Description of the offer : This PhD project supports the exploration of Vertical Compute’s vertical magnetic device concept. Thanks to the inherent high speed of magnetics and the vertical data
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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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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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research and soft robotics development. PhD project The PhD project will focus on the technical aspects of simulating the physics of the Drosophila larva body. The primary objectives include: Developing a
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study and other ongoing translational initiatives to develop a voice-based digital health solution to alleviate the diabetes burden. Project objective The PhD candidate will work at the interface
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Physics group (https://www.uni.lu/fstm-en/research-groups/theoretical-chemical-physics/ ) led by Prof. Alexandre Tkachenko at the Department of Physics and Material Science, we are looking for a PhD
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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