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on physiologic waveform analysis, biomedical signal processing, and computational modeling of continuous clinical monitoring data. The successful candidate will work on projects involving the analysis
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with neuroimaging and neural signal processing tools, including fMRI, structural MRI, diffusion MRI, EEG, or related modalities. Strong publication record in AI, machine learning, computational
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strategies for solid tumors. Our research spans both mechanistic and systems-level studies of cytokine and receptor signaling, T cell programming, cancer cell intrinsic immune evasion, and the tumor
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will develop and compare approaches for learning from sparse, noisy feedback generated during real use, including methods for multimodal signal integration, temporal identification of salient
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(GitHub) and AI coding assistants (e.g., Claude Code) Strong mathematical foundation relevant to quantitative image analysis (optimization, regression, statistics, signal processing, cluster analysis