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structural bioinformatics, machine learning, and high-performance computing, we will build the first Human Proteome-Wide Frustration Atlas — a resource to better classify genetic Single Nucleotide Variants
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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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23 Sep 2025 Job Information Organisation/Company Universitat de Barcelona Department Genetics, Microbiology and Statistics Research Field Biological sciences Chemistry Computer science Mathematics Other Researcher Profile First Stage Researcher (R1) Positions PhD...
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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 successful candidate will be joining the Quantum Optics Theory group led by Prof. Dr. Maciej Lewenstein. The successful candidate will work on Machine Learning research. Share this opening! Use the following
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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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techniques, machine learning, and Large Language Models (LLMs). Knowledge in Human-Computer Interaction (HCI) and Usability Engineering. High level of English (minimum B2). LanguagesENGLISHLevelExcellent
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) and satellite platforms, and surface energy balance models will be used to obtain evapotranspiration (ET); computer vision and machine learning techniques will also be used to identify and count fruits