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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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is to develop a highly innovative ‘Lab on a Bench (LoB)’ setup, integrated with Machine Learning algorithm, as a high throughput method for screening and developing formulated products that are used in
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learning that can generalize. Duties The PhD student will carry out research in the area of distributed machine learning The PhD student will actively contribute to setting up the research questions in
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state-of-the-art machine learning methods to analyse high-dimensional (time series) data. For the selected candidate, there will be possibilities to influence the project and develop new project ideas
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machine learning algorithms, so that the resulting AI model can run on a variety of devices, including UAVs (e.g. drones) that may be used in turbine inspection. The overall aim is the design of a portable
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, pre-operative determination via endoscopies and imaging remains unreliable for patient selection. The objective of this study is to develop an image-based machine learning prediction model to assess
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), consists of two main parts. First, the candidate will develop machine learning models aimed at improving the follow-up of neurocognitive function in critically ill children after discharge from the intensive
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Optimization and Machine Learning for Hydrogen Technologies The Natural Computing Group (NACO) at LIACS, Leiden University, is seeking a highly motivated researcher to join our cutting-edge project on AI tool
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) are looking for a: PhD Candidate on Multi-Objective Optimization and Machine Learning for Hydrogen Technologies The Natural Computing Group (NACO) at LIACS, Leiden University, is seeking a highly motivated
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; Midlands Graduate School Doctoral Training Partnership | Nottingham, England | United Kingdom | 27 days ago
the consumption journey. This exciting PhD Programme will look to address these challenges by employing a novel combination of data-donation, data-enhancement, and data-augmented laboratory experiments. The project