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changes and established markers for Alzheimer's disease. The project may also include machine learning methods to estimate individuals' biological age. The project is based on existing data from a prominent
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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to assess potato dormancy break, including: data collection, processing, AI model development and classification accuracy assessment. Involved in supporting an electrophysiology-based machine learning model
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passionate plant science researchers, bioinformaticians or remote sensing/data scientists with skills in image processing or phenotyping with a collegiate and self-driven attitude towards multidisciplinary
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KEK, QUP Position ID: KEK -QUP -POSTDOC19 [#30165, KEK-QUP-PD2025-1] Position Title: Position Location: Tsukuba, Ibaraki 305-0801, Japan [map ] Subject Areas: Data Science / Machine Learning
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10 minutes and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre
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looking for postdoctoral researchers in the area of computer vision, AI, and machine learning. The initial appointment will be for 2 years with a possible extension with a tentative start date in January
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. Responsibilities will include image data processing and analysis of PET data, and may include fMRI or DWI (MRI) data processing and analysis in tandem with PET data. Opportunities exist for integration of imaging
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UiO/Anders Lien 1st September 2025 Languages English English English Postdoctoral Research Fellow in Machine Learning Apply for this job See advertisement About the position Position as Postdoctoral