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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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the impact of past attempts to introduce PD as a treatment modality. The technology being developed in our lab is a biopharmaceutical device for rapid, on-demand compounding of the necessary dialysate, near
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. However, limited availability of peritoneal dialysate has limited the impact of past attempts to introduce PD as a treatment modality. The technology being developed in our lab is a biopharmaceutical device
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-aware multi-modal deep learning (DL) methods. At Argonne, we are developing physics-aware DL models for scientific data analysis, autonomous experiments and instrument tuning. By incorporating prior
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, AFNI, FSL, or similar products. Experience with one or more MR imaging modalities, including but not limited to: structural MRI, such as volumetrics and FLAIR-based white matter hyperintensities; resting
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brain aging and cognitive decline Utilize advanced computational methods, including machine learning and AI, to analyze neuroimaging data (e.g., fMRI, EEG, or other modalities) Develop and apply models
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include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow
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classes in the graduate and undergraduate curricula and/or similar classes, either in an in-person or online modality: ● Quantitative and Psychometric Methods ● Multivariate Statistics ● Measurement
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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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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