195 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" Fellowship positions in Norway
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to: compositional multiphase reservoir simulation upscaling or screening methodologies optimization of well positions and control strategies economic assessments machine learning or proxy-model based methods field
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responsible machine learning and/or human-AI interaction can be integrated with music-based forms of human creativity to contribute to health and well-being. The doctoral research should address one or several
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to investigate how responsible machine learning and/or human-AI interaction can be integrated with music-based forms of human creativity to contribute to health and well-being. The doctoral research should address
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. In addition, you must have: a solid foundation in energy technology and a strong understanding of artificial intelligence (AI), machine learning (ML), and data-driven modeling documented experience
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public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest in creative or artistic applications. Documentary evidence would be beneficial
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for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest
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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
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completed a doctoral degree in (machine learning, statistics, or similar). You must have a professionally relevant background in algorithms, machine learning, database systems, or data mining. Experience with
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level, developing and employing machine-learning tools for predicting antibody-epitope binding. In silico antibody design is a long-standing computational and immunological problem. Improving
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or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The appointment is a full-time position and is made for a period of three years