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on advanced machine learning and emulation approaches. Key responsibilities: The candidates will be expected to work on the following tasks: - Develop machine learning (ML) methodologies appropriate
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comprehensive platform for data extraction, analysis, and version control, providing access to highly curated datasets in a machine learning-friendly format. This PhD is part of the CARES project (Chemically
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different environments influence behaviour and wellbeing. Advanced analytics, including AI and machine learning, will be used to interpret behavioural and emotional data, enabling real-time insights
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machine-learning methods for sample segmentation and classification. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: The fellow will join the INESC TEC team within the LIBScan project, carrying
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international research environment covering a wide variety of research areas, such as algorithms and data structures, machine learning, computer graphics and vision, database systems, artificial intelligence
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different backgrounds. This position requires that you have graduated at Master’s level in in computer science, media technology, computer engineering, human-computer interaction, visual learning and
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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24th April 2026 Languages English English English The Department of Electronic Systems has a vacancy for a PhD Candidate in Distributed Machine Learning Apply for this job See advertisement This is
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for improved understanding of structural and kinetic processes in electrolytes; and machine learning concepts for improved analysis of experimental and simulated data. Material Synthesis Within this research
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Computer science » Computer systems Computer science » Programming Technology » Communication technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 26 Apr 2026 - 23