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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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MD or Ph.D. in Basic Science, Health Science, or a related field. No experience required. Preferred Qualifications PhD in computational science Working knowledge of machine learning and deep learning 3
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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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candidates to work on Bioinformatics and Computational Biology in Cancer Genomics and Immunology. This position will be involved in the development and/or application of computational approaches to understand
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using deep learning, computational chemistry, medicinal chemistry, chemical biology, and molecular cell biology to develop novel therapeutics to tackle complex diseases such as cancers. Successful
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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