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interest in cell biology (DNA repair field), microsccopy and processing of large datasets Strong English language skills – both spoken and written Eager to learn innovative approaches in data analysis
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of dissertation topics: Developing Remote Sensing–Based Indicators of Landscape State and Change Using Data-Efficient Machine Learning Across Scales Profile of the graduate The graduates have deep theoretical
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will be integrated with statistical and machine-learning methods to classify polarity states and identify quantitative signatures predictive of metastatic behavior. The project will deliver transferable
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that preserves object identity or style. They should have a solid publication record in top-tier computer vision conferences such as CVPR, ICCV, or ECCV, and demonstrate proficiency in deep learning frameworks
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, dimensionality reduction and/or machine learning methods (e.g., Lasso, ridge regression) is highly desirable. Familiarity with neurostimulation, Parkinson’s disease, or neuropsychological assessment tools is