359 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" Fellowship research jobs
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candidates will have specialist knowledge in signal processing and algorithm design, with experience in machine learning, AI system development and reinforcement learning along with a strong publication record
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clinical approaches, including: Histopathology and digital pathology (whole-slide imaging, WSI) Quantitative analysis of the tumour immune microenvironment AI-based image analysis, machine learning and deep
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related
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: Learn more about the innovative work led by Dr. William Shih here: https://www.shih.hms.harvard.edu/ . What you’ll do: Design nucleic-acid nanostructures and assemble them in a wet laboratory
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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their field of view, guided by their gaze. The success of this project will be critically dependent on the contributions of a researcher with expertise in human and machine vision. Qualifications The ideal
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interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list
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combinations of structural and functional properties, using both simulations for machine learning and experimental validation. Fabrication tools and methods are already established in our laboratory. Key
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approaches. Machine Learning in Geotechnical Engineering: Utilising data-driven approaches to model and predict soil-structure interactions or other complex geotechnical problems. Reliability-Based
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context. • Conduct statistical analyses, longitudinal modelling, or machine learning approaches as appropriate. • Develop documentation, codebooks, or tools to support reproducible research. • Lead