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the formula 0,40PQ + 0,40PV + 0,20AI. PQ corresponds to the quantitative evaluation of publications in ISI/SCOPUS journals: in advanced statistical models (e.g., Machine Learning), as well as in programming
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, whether actual or perceived by others (including service-connected disabilities), gender (including pregnancy related conditions), military status or military obligations, sexual orientation, gender
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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for interacting with colleagues and stakeholders. Department Specifics Develop various machine learning and data mining models including convolutional neural networks (CNNs), Transformers, large language models
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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data Experience with GIS/RS and database environments (e.g., ArcGIS and Quantum GIS) Experience with machine learning and statistical learning Experience working with large, diverse datasets Familiarity
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. Experience in machine learning methods is also required. Additionally, it is critical that the individual has experience in working with epilepsy patients, data collection via the NeuraLynx iEEG system, data
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computer applications used for data recording, analysis, and reporting. Physical Demands and Working Conditions Physical Activities Working Conditions Additional Information Remote Work: A hybrid remote work