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problems. This level of complexity increases when considering the multi-period operation of the system. These are difficult to solve using traditional strategies, so in recent years machine learning
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patient clusters and digital phenotypes, leveraging machine learning approaches to identify individuals at high CV risk based on clinical and biochemical markers, immune markers, digital health data (e.g
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, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to collaborating with researchers from other disciplines. The successful candidate will
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. The approach may also be complemented by machine learning techniques in collaboration with a Parisian laboratory. Ultimately, this functionality will be applied to molecular docking results, including correct
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specification and verification Theorem proving, familiar with proof assistants Machine learning and LLMs We offer Multilingual and international character. Modern institution with a personal atmosphere. Staff
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of the project is to use machine-learning assisted molecular dynamics simulations incorporating quantum effects for the identification of new variant-specific drug targets which will be validated experimentally
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found on hpc.uni.lu . The activities include classical HPC applications such as simulation and modeling, but also artificial intelligence and machine learning, bridging computational science, with data
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NeuroSchool, Aix-Marseille Université | Marseille, Provence Alpes Cote d Azur | France | 2 months ago
and novel conspecifics. Neural recordings will be analyzed using machine learning techniques, such as support vector machines and Bayesian decoders, to identify behaviorally relevant neuronal ensembles
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profile PhD (awarded within the last 5 years) of high quality, ideally in machine learning (in the broad sense), complemented by a strong mathematical foundation in probability and/or statistics Research
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Learning for High Entropy Materials”. In this position, the candidate will work on the development of machine learning models to explore the emerging class of high entropy materials. High entropy materials