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Study static spin structures and compute the dynamic (time-dependent) magnetization response, where the intermediate scattering function serves as the key neutron scattering observable Contribute
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Valorization, Sustainable Materials for Non-Pneumatic Tires, Sustainable Materials for Next Generation of Pneumatic Tires, Structure-Process-Properties Relationships. Do you want to know more about LIST? Check
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Valorization, Sustainable Materials for Non-Pneumatic Tires, Sustainable Materials for Next Generation of Pneumatic Tires, Structure-Process-Properties Relationships. Do you want to know more about LIST? Check
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of large-scale biomedical data, e.g., omics, clinical, structural bioinformatics, other biomedical data. It should be outlined in the CV Demonstrated skills and knowledge in omics data analysis
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SD-26045-RESEARCHER IN ADVANCED PLASMA-ASSISTED DEPOSITION PROCESS DEVELOPMENT FOR CATALYTIC THIN...
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? In the framework of a bilateral project
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complete application in English via https://jobs.liser.lu/jobs by including the following documents before April 15th, 2026 : Curriculum vitae ; Motivation letter ; Recent piece of research ; Copy of your
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graphs and related structures, limit theorems, stochastic calculus and applications, for example in machine learning and mathematical statistics Participation in the scientific activities of the department
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, economics, and other fields, united by a shared commitment to advancing sustainable technologies that benefit society. For more information, please visit our website: https://www.uni.lu/snt-en/research-groups
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satellite communications. Fields of applications range from 5G/6G telecommunications to satellite-based internet connectivity. For details, you may refer to the following: https://wwwen.uni.lu/snt/research
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by integrating large-scale single-cell foundation models with structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under