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. Demonstrated high level of achievement in related research productivity and academic writing. Technical skills in computer programming, algorithm development and deep learning model implementation, and practical
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours ago
. Special Physical/Mental Requirements Campus Security Authority Responsibilities Not Applicable. Special Instructions Quick Link https://unc.peopleadmin.com/postings/311797 Posting Contact Information
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point-based PhorEau projections using a machine-learning model predicting tree species richness as a function of spatially explicit abiotic and biotic covariates, including satellite-derived data
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- Department of Electronics and Information Systems Degree Master in Informatics, Master in Computer Science, Master in Computer Engineering, or similar Occupancy rate 100% Vacancy type Research staff ABOUT
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for the PhD admission is available at TalTech´s web-page: https://taltech.ee/en/phd-admission The following application documents should be sent to tarmo.soomere@taltech.ee CV Motivation letter Degree
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field. Have proven expertise in statistical modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in
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/Administrative Internal Number: 6821378 Research Data Scientist About the Opportunity About the Institute Do you want to be part of an exciting new Institute focused on the fusion of human and machine intelligence
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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machine learning models. Working with extremely large, multi-modal datasets. Prior experience in analysis of clinical health records, and time series data are highly preferred. Qualifications Requirements