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network inference and modeling, machine learning and deep learning. Experience in working with Arabidopsis and plant genome data is a strong plus. The position is expected to continue for multiple years
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Nutrition Postdoc Appointment Term: Fixed term for one (1) year with opportunity for renewal Appointment Start Date: ASAP Group or Departmental Website: https://colmanlab.stanford.edu/(link is external) How
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positions. The postdocs will support an exciting new project that is focused on autonomous, soft, tip-extending robots for stroke treatment. The overall goal is to enable fully autonomous navigation
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to present their work and learn from others. Fellows are also encouraged to engage with colleagues and attend departmental seminars. Applicants must demonstrate outstanding scholarly achievement and promise
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) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing spontaneous versus precipitated withdrawal episodes. The spontaneous vs
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engineering and clinical physiology. Projects may involve signal quality assessment, artifact detection, waveform segmentation, feature extraction, hemodynamic modeling, time-series analysis, machine learning
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applications. Research activities may involve geophysical forward modeling, AI-driven geophysical inversion, seismic monitoring and imaging, scientific machine learning, depending on the specific research focus
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county across the state, Texas A&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about
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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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-cell or spatial transcriptomic analysis is desirable. Experience with machine learning, LLMs, AI agents, multimodal data integration, or automated biological interpretation workflows is desirable but not