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and data processing skills: experience of programming in one or more languages (e.g. R, C/C++, Python, Matlab). Practical experience of algorithm development and implementation of machine learning
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typologically diverse languages Creating self-supervised learning algorithms that can assess phonological development and speech complexity in children from birth through age 6, with applications to both typical
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to the construction of the detector at the LNGS. Data taking should start in 2029. The subject of this postdoctoral position, funded by the CNRS for two years, is to prepare the analysis of the first data in order to
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structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under budget and time constraints, facilitating flexible adoption
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on developing advanced methods for semantic structure extraction, conceptual and argumentative flow reconstruction, rationale-aware content generation, metacognitive prompting, and adaptive personalization. Core
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of computational biology, Genomics, machine learning, and data science, contributing to the development and evaluation of advanced algorithms for analyzing large-scale biological datasets. This role is ideal
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. The ideal candidate will have: Experience in developing novel algorithms. Experience in coding in python and preferably C/C++. Experience in frontend engineering, including but not limited
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staff position within a Research Infrastructure? No Offer Description The selected candidate will develop innovative and efficient resource optimization algorithms, suitable for this context, with cost
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Requisition Id 15721 Overview: We are seeking a Postdoctoral Research Associate who will contribute to the development and implementation of novel quantum algorithms for materials simulation, with
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and leukemias (in particular Hodgkin lymphoma and hairy cell leukemia), and to translate this knowledge in the clinic by developing new precision diagnostic and therapeutic tools (as exemplified by