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Field
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Engineering is seeking a Postdoctoral Research Associate focused on optical signal analysis and biomarker development. Data from human subjects will be analyzed to determine brain health as well as identify
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the following directions: 1) Developing computational methods for integrating multi-modal data, such as scRNA-seq, scATAC-seq, spatial transcriptomics, ChIP-seq, and CRISPR screening. 2) Investigating context
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research is based on large and high-dimensional datasets across multiple modalities, including molecular, clinical and histopathology imaging data. Our computational pathology research is based
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Dr. Dustin D. Benac and faculty affiliated with the initiative. We are seeking one postdoctoral research associate with expertise and interest in partnering on the analysis, writing, and dissemination
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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves
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Dr. Dustin D. Benac and faculty affiliated with the initiative. We are seeking one postdoctoral research associate with expertise and interest in partnering on the analysis, writing, and dissemination
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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practices in different research communities; Teach lessons and workshops such as data processing and analysis using R or Python, tools and best practices for data management, computational best practices
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-modal data processing for real-world robotic applications. Strong background in deep learning, supervised and unsupervised learning, time-series analysis, information visualisation, with experience in
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development and characterization of nucleic acids products including various RNA modalities. This is a unique opportunity to be trained in nucleic acid quality assessment, Next-generation sequencing and data