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: Design and train vision–text transformer architectures for multimodal fusion (RGB + thermal, intraoperative video, OR signals, EHR, surveys); develop temporal and cross-attention components
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research. Prepare and write research papers, presentations, grant proposals. Train Graduate Students. Qualifications: PhD in Computer Science or related field (completed or near completion) Strong
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transformer architectures for multimodal fusion (RGB + thermal, intraoperative video, OR signals, EHR, surveys); develop temporal and cross-attention components for longitudinal risk trajectories. Build robust
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mathematicians, and domain scientists Develop software that integrates machine learning and numerical techniques targeting heterogeneous architectures (GPUs and accelerators), including DOE leadership-class
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this diversity. Our research spans comparative genomics, chromatin architecture, gene expression, protein abundance, and metabolite profiling—combined with computational biology, machine learning, and advanced
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Model measurements, and searches for new physics and performance studies. Candidates with experience in modern AI/ML methods—such as transformer architectures, tokenization strategies, and embeddings
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Affairs. The FY25 minimum is $76,383. The research group led by Dr. Zihuai He (https://profiles.stanford.edu/zihuai-he (link is external) ; https://www.zihuai-he.com/ (link is external) ) at Stanford
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growing across an array of common gardens in the California Sierra Nevada that are part of the Adaptive Management Experiment (https://www.adaptive-forest-management-experiment.com/ ). Relevant phenotypes
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Status Full Time Posting Number 26FA0173 Posting Open Date 03/01/2026 Posting Close Date Qualifications Minimum Education and Experience The individual must have completed a PhD in biology, biochemistry
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Status Full Time Posting Number 26FA0173 Posting Open Date 03/01/2026 Posting Close Date Qualifications Minimum Education and Experience The individual must have completed a PhD in biology, biochemistry