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We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative
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livable cities. The project will be based in the AI Laboratory for Molecular Engineering (AIME) , led by Assistant Professor Rocío Mercado Oropeza, where researchers develop new machine learning (ML
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. The project will be based in the AI Laboratory for Molecular Engineering (AIME) , led by Assistant Professor Rocío Mercado Oropeza, where researchers develop new machine learning (ML) methods to tackle
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multidisciplinary research in energy markets, optimization, game theory, and machine learning. Our team of 13 members (link ), from 10 different nationalities, values diversity and includes experts from a range of
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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. Applying machine learning to New Zealand’s landslide inventories to model landslide location, character and dynamics. Integrating time-series and inventory data to develop new models to predict location
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models. The scientist will conduct research using machine learning and classical parameterization methods on data from ocean gliders equipped with microstructure turbulence sensors, turbulence resolving
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aircraft, utilized for research into thermal management and system health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical
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(Kingdom of the) [map ] Appl Deadline: 2025/06/30 11:59PM (posted 2025/06/11, listed until 2025/12/11) Position Description: Position Description Joint-PhD Position on Advancing Machine Learning Methods
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algebraic geometry, or representation theory; familiarity with programming and the use of computer algebra. Our offer A position for 18 months, with an extension to a total of four years upon successful