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to have a strong interest in data analysis, and medical research, along with relevant academic background and skills within medical image analysis and machine learning that will enable them to contribute
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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
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accurate information. Machine learning allows for the systematization and processing of this data into new forms of information to support the management of forest resources and ecosystems. The PhD candidate
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for this position focused on machine learning (ML). This position offers a unique opportunity to conduct both basic and applied research in collaboration with Brookhaven Lab staff, the Department of Energy (DOE), and
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one of the following areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or
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Computer Vision There is growing trend towards explainable AI (XAI) today. Opaque-box models with deep learning (DL) offer high accuracy but are not explainable due to which there can be problems in
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fundamentals, including image processing, pattern recognition, and 3D geometry (share your GitHub profile) LanguagesENGLISHLevelExcellent Research FieldEngineering » Computer engineeringYears of Research
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17 Oct 2025 Job Information Organisation/Company ETH Zürich Research Field Chemistry » Other Engineering » Chemical engineering Engineering » Computer engineering Engineering » Electrical
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-weighted and functional MRI, intracranial EEG) Multi-scale modelling of human brain development Using machine learning frameworks to interrogate the relationship between brain development and cognitive
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. Correlating experimental, ab initio and multi-scale simulation as well as machine learning techniques is central to our mission: Development and application of advanced simulation techniques to explore and