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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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at the intersection of computational modeling, data science, and clinical medicine. The successful candidate will work closely with clinicians, intensivists, and computational scientists to develop
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biology approaches. Experience with HPC or cloud computing environments for large datasets. Equipment Utilized Physical Demands and Work Environment Overview Statement Posting Details Special Instructions
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preferred. Experience with atmospheric models (e.g., GEOS-Chem, CMAQ) and skills in python, Fortran and high-performance computing are also desired. Position Status Full Time Posting Number 25FA0918 Posting
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degree in Cognitive Science/Psychology, public health, computer science/artificial intelligence (AI), informatics, or a related field required. Qualified candidates must be in the process of completing
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molecular biology and cancer biology, required. ABD candidates may be considered; qualified candidates must be in the process of completing or have finished the training for Ph.D. and/or M.D. Candidates must
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communicate in English to sufficiently perform the job duties. Must be computer literate with proficiency and working knowledge of database and reporting tools such as Microsoft Word, Excel and PowerPoint. Must
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practices relating to the education of young children birth to age 8 and those ages 3 to 5, in particular. Equipment Utilized Computer literacy including spreadsheets, webinars, and statistical programs
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various genomic datasets Effective spoken and written English required. High level of computer literacy required. Preferred Qualifications In-depth understanding and hands-on experience in RNA-seq and ChIP