68 parallel-computing-numerical-methods-"Simons-Foundation" positions at Nature Careers in France
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funding in the relevant fields of data science Enthusiasm for applying advanced data science methods, including AI-based approaches to environmental challenges and scientific evidence synthesis Technical
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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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Ph.D. STUDENT (F/M/D) to study weak covalent bonds in MXene nanoconfinement for battery applications
for materials research, a scientific partner to national and international research institutions, and a research and development provider for numerous companies throughout the world. The INM is a member of the
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for methodological development in the project centres around demonstrating the feasibility of the use-cases with minimal data-sharing and via methods that concentrate on anonymisation, federated learning, and data
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ExpoSignalz Project: An exciting research project funded by the European Union’s Horizon Europe Research and Innovation Programme The aim of the ExpoSignalz Project is to investigate how exposure
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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-resolution imaging methods is a strong advantage Strong computational and organizational skills, with attention to detail, particularly in experimental planning, documentation and sample management A high
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to the development of digital and face-to-face methods for public involvement, by shaping the theories, methodologies, and tools that underpin participatory knowledge production in human services. Active in research
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policies. The University of Luxembourg aims to play a key role in this public-facing co-productive knowledge landscape. This position will contribute to the development of digital and face-to-face methods
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Exploit an existing clinical database containing numerous follow-up FDG/PET exams o Develop modeling methods for the time-series analysis of PET-CT data o Develop a methodological formalism for integrating