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Field
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/Python/LabVIEW for data analysis and software experimental control. Also required are strong written and oral communications skills, interpersonal skills for collaborative science and mentorship, problem
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of future research proposals. Skills, Experience & Qualifications Needed PhD in an appropriate subject area (awarded or submitted). Proficiency in Python for scientific computing, including basic scientific
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
Experience Applicants must have experience writing and modifying scientific code, performing data analysis or simulation workflows, and proficiency in at least one programming language such as Python, C, C
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Education, STEM Education, Statistics, or a closely related field. Experience conducting quantitative analysis using statistical software such as R or Python. Experience conducting educational, social science
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relevant to modern data science (e.g., Bayesian or frequentist inference, information theory, uncertainty quantification, high-dimensional methods). Programming skills in Python and/or R, with evidence of
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models, transformers, representation learning, contrastive methods). Solid experience with Python and Pytorch and good command of software development tools such as GIT. A good track record of authoring
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, and sleep stages using Python Contributing to and shaping cross-species computational modeling Leading publications and presenting results at international conferences Mentoring junior researchers and
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cancer biology, molecular/cellular biology, genomics, or immunology with expertise in gene editing technology and NGS; flow cytometry and cell sorting; and bioinformatic and data integration, R/Python
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proficiency in R, Python, or MATLAB. Familiarity with stem cell culture or GPCR biology is beneficial. Online Application Required Documents Curriculum Vita Name and Contact Information of References Letters
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intervention and data from diverse sources Proficiency in statistical and computational languages (SQL, SAAS, R, Python, etc.), skills Knowledge of both traditional statistical analysis (e.g., logistic