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have affinity with data collection tools? Within the project ReGeNL, we are looking for a junior researcher to support the monitoring and learning activities within ReGENL. There is steadily growing
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/coding and experimental hardware skills are desirable. Strong analytical and mathematical skills. Passion for research and willingness to learn. Good presentation, communication and scientific writing
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$230.7m of external research funding in 2022, and is the recognized leader in experience-driven lifelong learning. It has campuses across the United States and Canada (in Boston; Charlotte, North Carolina
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Position Description The project will focus on the development and application of advanced data-analysis techniques for gravitational-wave science, including machine learning and deep learning
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evaluation of pharmacological therapies under the supervision of Dr Rogier Min. At the National Research Council of Italy (CNR) in Cagliari, you will learn computational chemistry approaches to identify drug
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; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting pathogen invasion success and plant
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than late in the utterance. You will learn to use multiple methods, including artificial language learning and EEG, collecting data from different language communities, including indigenous language
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, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a specific subject see General syllabus
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or environmental engineering, Mathematics (Operations research) or Computer Science or Machine Learning). Documented knowledge of relevant methodologies, both quantitative and/or qualitative, at master’s level
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of mill and production operations. The scientific challenge will be to use the model and machine learning alongside live mill data (temperature, rolling loads etc) to reverse engineer the current