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and production of software tools for in silico screening of chemical libraries and rational drug design of molecules for therapeutic purposes. - Contribute to the development of a high-throughput
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for a duration of six years. NumPEx contributes to the design and the development of numerical methods, software components and tools that support future productive European exascale and post-exascale
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of the project is to design, model and simulate neural networks based on magnetic skyrmion nucleation and propagation. The second objective is to fabricate these hardware neural networks, characterize
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Required knowledge: - Degree: PhD, Engineering - Continental biogeochemistry - Environment and professional networks - Organization and functioning of higher education and public research - Language: English
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teams aim to increase the diversity and dynamism of data, services, interaction devices, and use cases in order to influence the evolution of software and systems to guarantee essential properties such as
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has a strong societal impact ambition and requires particular care to protect intellectual property, while maintaining a collaborative research approach within a network involving other academic and
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transcriptomics data and network-theoretic approaches. - design of a new mathematical method - monitoring and study of publications relevant to the field - programming/coding in Python (Pytorch) - presentation
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research group of 6 permanent staff members, 3 PhD students and 2 non-permanent researchers within the Electronics team. He/she will also collaborate with other teams on campus, in particular the CIMAP
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Information Eligibility criteria Applicants should hold a PhD in theoretical chemistry, physics, materials science, or a related field; -demonstrate strong expertise in machine learning (regression, neural
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experimental validation of mathematical and computational models linking individual microscopic dynamics, information propagation, and collective structures (norms, social networks, global performance