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Field
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apply machine learning algorithms with special attention to digital footprint reduction and data privacy. Functions to be developed: Develop methodologies and experiments to measure and optimize
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(Mandatory): Machine Learning Statistical Modeling Data Visualization Academic Writing Languages (Mandatory): English: IELTS 7.0 or higher LanguagesENGLISHLevelExcellent Research FieldComputer science
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Description Implement and validate machine learning models and statistical algorithms for data imputation, anomaly detection and uncertainty management in geospatial environments. Collaborate in the preparation
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physicsEducation LevelMaster Degree or equivalent Skills/Qualifications A Master’s Degree in Physics or similar. Specific Requirements Experience in big-data management and analysis, with solid machine learning
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integrations, and collaborating with the team to refine detection strategies and performance metrics. Tasks to be performed Literature review on scam detection, blockchain security, and machine learning methods
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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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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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inteligencia artificial/machine learning. Tecnologías IoT y sistemas distribuidos. Conocimientos en FPGA. // Knowledge of artificial intelligence/machine learning, oT technologies and distributed systems, and