13 machine-learning-"https:"-"https:"-"https:"-"https:" Postdoctoral positions at Baylor College of Medicine
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, and other methods. Collects data using cameras, sensors, and data acquisition systems. Prototypes, troubleshoots, and fine-tunes machine learning models for outcome predictions relevant to surgery
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implements machine and deep learning programs. Develops algorithms to deconvolve RNA-seq data and compare them to AI-based methods. Performs follow up validation efforts on cell lines. Minimum Qualifications
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research protocols and procedures, including in computational tasks where data visualization, preprocessing, or interpretation can be improved. Devises and deploys custom machine learning approaches where
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candidates with a proven track record in developing open-source machine learning, deep learning, or cheminformatics tools (Preferred written in Python). Job Duties Plans, directs and conducts research
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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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the Texas Children's Cancer Center. The project aims to develop and test novel CAR-redirected immunotherapy for pediatric solid tumors. In particular, we want to design and test a regulated PRDM1 knockdown in
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, during, and after their military service, and any of these violent experiences may have resulted in brain injury. Because these types of experiences are rarely reported, it is likely that these brain
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models and machine learning. Experience in epigenetics or gene regulation is a plus, and experience with statistical analysis tools such as R or Python is recommended (successful candidates will be
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, national, and international meetings, and reading current primary literature. Provides a friendly working environment and be available to teach laboratory techniques and scientific methodology to research
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next-generation CAR T-cell therapies for pediatric solid tumors. The fellow will apply high-throughput screening, T-cell engineering, and single-cell analytics to identify and validate novel receptor