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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
or equivalent experience in machine learning or a related quantitative field (Computer Science, Artificial Intelligence, Statistics, Mathematics, Physics, Computational Biology/Chemistry). Candidates will be
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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of machine learning and advanced molecular dynamics techniques for molecular simulations and to study Nucleic acids structures and their interactions. For more information, please visit https://nyuad.nyu.edu
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, machine learning or neuronal population analyses would be an advantage. Specific Requirements We are looking for a candidate with a strong interest in scientific software development and quantitative
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warmer and wetter world. RAPTURE brings together high resolution physical simulations, machine-learning climate emulators, and new perspectives on the dynamics of weather and climate to understand i) what
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Attributes for Success: Bachelor's, master's degree, or PhD in Artificial Intelligence, Machine Learning, or related computing or physics field and up to 2 years of relevant experience, equivalent combination
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AI and data science, particularly in dynamic settings where observations are collected sequentially and decisions influence future outcomes. This project will develop novel machine learning and
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Architecture, Planning and Management at the Swedish University of Agricultural Sciences (SLU) seeks a driven and committed PhD student with a focus on how governance structures, decision flows, departmental
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Strong skills in simulation methodologies Excellent communication and interpersonal skills Desirable Criteria: Familiarity with machine learning algorithms and artificial intelligence as applied
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técnicas de machine learning e IA. Sólidos conocimientos en análisis y tratamiento de datos, programación y desarrollo de modelos analíticos. Experiencia con bases de datos y herramientas de análisis