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Field
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by information and communication technology which could lead 20% of global energy production to be consumed by the adoption of artificial intelligence. Therefore, “unconventional” computing
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Epidemiology of Malaria), led by Aimee Taylor. Using simulation-based inference (SBI) with deep learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum
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models, whilst respecting the specific spatial structure induced by river networks. - Cleaning, structuring and analysing historical long-term monitoring data (approx. 200 sites). - Adaptation and
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, annotate and analyse metabolomic data using dedicated pipelines (construction of molecular networks, querying spectral databases, in silico annotation, calculation of metabolic diversity indices). Contribute
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field. Draft and format notes, documents and/or reports related to the relevant area of expertise. Communicate in English. Speak in public. Transfer technical expertise and professional practices. Work as
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to the dissemination of ultra-stable frequency and time references over telecommunication networks. Its optical-fiber network and laser stations also provide an experimental platform for the development of new
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toxicology. The successful candidate will benefit from access to state-of-the-art facilities for additive manufacturing, cell culture, microscopy and biomaterial characterization, as well as a network of
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. • Get familiar with existing libraries for working with tensor networks in the Julia programming language (ITensors.jl, Tensor4all.jl, …). • Implement different tensor network topologies (e.g. tree tensor
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determines observables of the replication program such as the Mean Replication Timing (MRT) and the Replication Fork Directionality (RFD) profiles. We proposed a strategy to train a neural network to infer
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. The LEAPS ULTRAFAST network announces the launch of the first call for applications for its prestigious ULTRAFAST postdoctoral program. This postdoctoral fellowship programme is co-funded by