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at the intersection of neuroscience and AI, with opportunities for innovation and collaboration across multiple disciplines. Candidates are expected to have experience in cutting edge AI technologies and their
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, the development and fine-tuning of vision foundation models, multiple instance learning, survival analysis, and interpretable model development. You will also lead efforts in building multimodal deep learning
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, the development and fine-tuning of vision foundation models, multiple instance learning, survival analysis, and interpretable model development. You will also lead efforts in building multimodal deep learning
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description The PhD project aims to explore how multiple layers of gene expression regulation—including DNA packaging, transcription initiation, and translation—interact to control gene activity. Using
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, clustering), statistical modelling, and other computational techniques Process large scale text data sets in multiple languages Create documentation for data and processes guided by principles
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to identify novel targets for diagnostic use and therapeutic intervention. Fellows will work on research problems using rich data sets and leading-edge analytic approaches supported by multiple NIH grants (R, U
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is also expected to re-implement historical narrative systems in Python and help determine the course of a larger collaborative CNS project dealing with such systems. About the LEAD AI fellowship
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Open Source Geospatial software and libraries, e.g. GDAL or other open source geospatial packages under OSGeo; Experience in programming with multiple languages (e.g. Java, C/C++, Python) for geospatial
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in coding, i.e. MATLAP, Python, etc. Salary Range $61,008+ depending on NIH level Working Conditions May work around standard office conditions. Repetitive use of a keyboard at a workstation. Required
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Generative AI for career growth and entrepreneurial success. The ideal candidate will be a detail-oriented researcher capable of managing multiple large-scale projects simultaneously. You will take ownership