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on developing advanced new algorithms, testing and validation, and applications in medical neuroimaging and non-imaging modalities. The candidate will contribute to the overall research goals and objectives
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, applying state-of-the-art sensing technologies and self-developed algorithms. Minimum Qualifications • Ph.D. in Mechanical or Industrial Engineering, and other fields that explore Artificial Intelligence
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Job Description Apply now Job Title: Postdoctoral Associate Division: Molecular and Human Genetics Work Arrangement: Location: Houston, TX Salary Range: Per NIH Guidelines FLSA Status: Exempt Work
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the following objectives: 1. Characterize 3-D Urban Structure and Change: Utilize data from multiple remote-sensing platforms and deep learning algorithms to generate high-resolution maps of 3-D urban structure
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applications. Hands-on work with Verasonics Vantage or similar programmable ultrasound systems. Practical experience implementing image-reconstruction algorithms. Demonstrated skill in handling mouse and rat
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will apply state-of-the-art machine learning algorithms and custom disease-relevant genomic datasets (e.g., coronary artery single-nucleus chromatin accessibility and RNA sequencing) to develop targeted
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genetics and genomics, with expanded interests in computational biology, functional genomics, and neuroscience. Example projects within the university and with external partners: ⢠Noncoding Variation in
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with Verasonics Vantage or similar programmable ultrasound systems. Practical experience implementing image-reconstruction algorithms. Demonstrated skill in handling mouse and rat neonates or adults
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, computational genomics, functional assays, and integrated data analysis. We are seeking a highly motivated Postdoctoral Researcher who shares our passion for solving foundational problems in human genetics and
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learning algorithms into professional software with an intuitive user interface, incorporating feedback from CHWs through iterative design and evaluation cycles. The selected candidate will be part of a