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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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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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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
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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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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, traditional risk prediction models like the Steno Type 1 Risk Engine fail to account for the immunological dysregulation inherent in T1D. Project Objective The PhD candidate will primarily focus on the clinical
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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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The SiMul team (https://cran-simul.github.io) at the University of Lorraine is offering a fully funded PhD position on the theoretical foundations of self-supervised learning, focusing