30 computional-geometry-algorithm Postdoctoral positions at Baylor College of Medicine
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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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learning algorithms and creating predictive models. This role will contribute to evidence-based processes and procedures for program quality review and assessment of outcomes data as well as develop
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a diverse team of biological and chemical scientists Experience with high performance computing environment (HPC) / cluster job submission Knowledge of statistical methods, data science algorithms
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field (e.g. statistics, computer science, or quantitative biology). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming
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computer science. These skills would be applied to large mass spectrometry and mass spectrometry imaging datasets for clinical research, focusing on malignancies including breast and lung cancer and intraoperative
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. The goal of the Training Program at the CNRC is to prepare Ph.D. and M.D. postdocs for biomedical research careers in nutrition that focus on pregnancy, lactation, infancy, childhood, and adolescence
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AI-modeling and coding. The successful candidate will work alongside a multidisciplinary team, leveraging artificial intelligence and computational methodologies to optimize treatment plans, enhance
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with robots, computers, especiallyzed software and stereomicroscopes in addition to the genetic and molecular biology benches. Job Duties Conducts genetic screens using Drosophila disease models
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intended for life science graduates from Immunology or Microbiology backgrounds, however, a graduate with background in Computer Science or Computational Biology will also be considered. The successful
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. Experience with computational analysis of NGS sequencing data and/or experience with mouse models is a plus. Job Duties Under the general direction of the PI: Design, plan, and conduct research experiments