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Field
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. Measurement techniques in field applications and in the laboratory. Modeling and simulation skills (batteries, energy systems, electric equivalent circuits). Machine learning, statistical analysis, and other
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used in producing fine chemicals, including pharmaceuticals. By leveraging state-of-the-art advances in computer vision and machine learning, we aim to manipulate Particle Size and Shape Distribution
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the laboratory. Modeling and simulation skills (batteries, energy systems, electric equivalent circuits). Machine learning, statistical analysis, and other contemporary data-driven techniques. Computational
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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on leveraging deep learning and advanced image processing techniques to improve the current tools for biomonitoring of aquatic ecosystems. This position involves the development and application of machine
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Qualification type: PhD Location: University of Hull Funding for: UK students Funding amount: £20,780 Hours: Full time Closes: 9 May 2025 Subject areas Engineering & Technology Computer Sciences Mathematics
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for data-efficient exploration and optimization within the process parameter space as well as for adaptive, data-driven machine learning to map the electrolysis process to a digital twin. Data workflows and
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employment. Starting date: 10.02.2025 Job description:PhD position in atmospheric corrosion studies via novel experiments and machine learning Reference code: 50134137_2 ? 2025/MO 1 Commencement date: as soon
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application of machine learning algorithms to automatically classify freshwater benthic diatoms at the species level and quantify key morphological traits. These advancements aim to improve ecological
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Overview Nature offers a mechanism - called homeostasis - by which life forms can maintain their physical integrity and well being. On the other hand, a series of machines, including robots, cannot