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fragments (e.g., JavaScript, Python, C#) to augment platform logic and address limitations Preferred Educational Qualifications An advanced degree from an accredited institution of higher education in a
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post-processing and analytics skills using Matlab, python or similar programming language Have a strong experience of using design software and fabrication tools, such as CNC Have strong project
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molecular dynamics simulations, applicable to materials science, biomolecules, or a related field. Programming experience (e.g., Python), with a strong background in developing and applying computational
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deadline Experience with urban acoustic monitoring or transportation noise assessment Programming skills in Python Knowledge of machine learning techniques applied to acoustic or environmental data
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representation learning. You have strong programming skills, especially in Python, and preferably experience with PyTorch. You have a track record of publishing in top image processing / computer vision journals
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assistants • Write scientific publications and present findings Required Qualifications • MA in computational social science, digital humanities, computer science, or related field • Python proficiency
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 16 days ago
modelling, and/or gene-environment interaction studies would be beneficial but not required. Prior training and experience with R or Python, manuscript and grant writing, project management, and ability
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
experiments to understand and improve tool performance, and – most importantly – by summarizing findings in white papers and application notes. A full job description can be found here: https://mitnano.mit.edu
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research impact. More information about the study can be found here: https://www.healthdata.org/research-analysis/gbd . Purpose of the post We seek a motivated, detail-oriented researcher enthusiastic about
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preclinical datasets, including data extracted from electronic health records, using Python, R, and other relevant tools. Applies statistical and machine learning methods (e.g., descriptive statistics