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platforms include GRO-seq, RNA-seq, ChIP-seq, ATAC-seq, CRISPR-seq, single-cell RNA/ATAC-seq, microC, machine learning, sophisticated mouse genetic tools, and an ex vivo tissue culture system from patients
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will work closely with Drs. Audrey Hendricks and Ryan Layer as well as grad students, postdocs, and other collaborators to develop and implement statistical and machine learning methods, software
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cross-sectionally. * Developing and applying machine learning and AI approaches to identify interactive topological relationships between various imaging modalities and multi-omics during aging and
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disseminate research results and data in peer-reviewed publications as well as presentations at international conferences. Required Qualifications: Education/Training- PhD in Electrical and Computer Engineering
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, fluorescence in situ hybridization, and bioinformatics. Preferred Qualifications Molecular biology and genetics laboratory experience; web computer skills; ability to learn new techniques and procedures
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economics; food and agricultural economics; and international and development economics. Faculty members in the Dyson School frequently collaborate with colleagues in Computer and Information Sciences
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, unlocking reliable perception and navigation where GNSS/GPS cannot be trusted or is unavailable. The project combines ultrasonic sensing, probabilistic perception, and machine learning with advanced robotics
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Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived experiences. Embracing
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background in one or more of the following areas: dynamics analysis of power systems, machine learning, cybersecurity, renewable energy, microgrids, hands-on experiences on hardware-in-the-loop projects
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, and organize all data from depositions, characterizations, and property measurements. (6) Organize all data and learning into scientific manuscripts, quarterly reports, and presentations. (7) Coordinate