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Field
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looking for a professional to support research projects in the area of Zero-Knowledge Proofs (ZKPs), especially in its implementation in Machine Learning (ML) models. Main tasks: Literature review on ZKPs
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the simulation of mechanotransport in 169 patient-specific disc models using Abaqus, with the aim of extracting biomechanical data and mRNA expression profiles. Subsequently, a machine learning analysis will be
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The Center for Machine Learning Research (CMLR) is a newly founded interdisciplinary research center at Peking University. Its goal is to advance machine learning-related research across a wide
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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | 10 days ago
). - Artificial intelligence and machine learning. - Advanced programming in Python and use of machine learning/bioinformatics libraries. - Software development and database management. - Ability to work in
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“Heterogeneous Advances in Machine Imitation Learning for Training Orchestrated Navigation (Hamilton)” The CVC offers one pre-doctoral fellowship linked to the project “Heterogeneous Advances in Machine Imitation
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(Machine Learning Force Fields, ML-FF) to simulate gas-phase fragmentation processes via molecular dynamics. Design and maintain a project-focused results database (schema, metadata, upload/retrieval scripts
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integration of the project webpage into the institutional platform Uso de machine learning para estimar propiedades geomecánicas del terreno a partir de datos de laboratorio/ Use of machine learning to estimate
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learning. Professional Experience: Have worked using Machine learning. Programming in C, C++. Experience in functions similar to those described will be valued, specifically in the development of research
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selection process for an indefinite employment contract within the framework of a Line of Research Research line: Machine learning applications https://www.upv.es/entidades/SRH/conypi/A1268833.pdf Where
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processing image datasets for individual and behavior detection. - Defining, training, and validating Machine Learning models. - Collaborating in general research tasks. Where to apply Website https