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Field
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learning techniques for tool health monitoring and prognosis. Dissemination of research results through scientific publications, conference presentations, and completion of a PhD thesis. Required skills
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University of Girona (UdG) - Institute of Computational Chemistry and Catalysis (IQCC) | Spain | 2 months ago
(CompBioCat) research group at the Institute of Computational Chemistry and Catalysis (IQCC, http://iqcc.udg.edu ), University of Girona (Spain), is seeking a highly motivated PhD candidate to join the ERC
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Python programming. ● Experience in monitoring code performance. ● 3 or more years of demonstrable experience in machine learning theory. ● Excellent communication and teamwork skills. ● Proficiency in
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Balears (UIB) Where to apply Website https://ppi.uib.cat/inici/ Requirements Research FieldAstronomy » AstrophysicsEducation LevelPhD or equivalent Skills/Qualifications A PhD in Physics, Astrophysics
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FieldEngineeringEducation LevelMaster Degree or equivalent Skills/Qualifications - Inteligencia Artificial y Aprendizaje Automático: Conocimientos en modelos de IA, Machine Learning y Deep Learning. Se valorarán muy
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practical knowledge of statistical and programming packages is mandatory, including R, Python, and/or SQL. Extensive experience with advanced statistical techniques and algorithms, such as Machine Learning
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..................................................................................................... up to 15 points <b>Machine</b> <b>learning</b> and optimization algorithms ............................................................... up to 10 points Section 3: Other Merits – up to 5...
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master in Computer Science, Bioinformatics or related field Strong programming skills in R Background in machine learning and/or protein structures Fluent in English Specific Requirements Mobility rule
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ion transport, degradation, and safety. The doctoral candidate will use quantum-mechanical simulations, complemented by advanced machine-learned potentials, to model how charge, atoms, ions, and defects
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to research projects involving big data analytics, artificial intelligence, and machine learning applied to stroke care. Support the development and validation of predictive models and clinical decision-support