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applications from researchers specializing in probabilistic and neuro-symbolic AI. Areas of interest include, but are not limited to: • Probabilistic machine learning • Deep probabilistic graphical models
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The Department of Public Health at Faculty of Health at Aarhus University invites applications for a position as Associate Professor in the field of statistical and machine learning methods
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to join our Copenhagen Section. The research profile of the applicant should be within mathematical foundation, verification tools, validation methodologies, probabilistic graphical models and machine
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/PhD) You can learn more about the recruitment process here . Applications received after the deadline will not be considered. All interested candidates irrespective of age, gender, disability, race
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of novel biostatistical and machine learning methods for healthcare data. Building and mentoring a strong research group in data science methods. Collaborating with clinical researchers and public health
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medical images and other health data. The group develops and evaluates clinically meaningful decision support tools by integrating health data, domain knowledge, and machine learning. Key objectives include
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include data science management and development of novel and executing existing computational methods including machine learning and deep learning methods to integrate genomics, transcriptomics and
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Assistant Professor in Electrical Energy Technology, Department of Electrical and Computer Engine...
. Supervising student projects and theses, particularly within converter technologies, electrolysis integration, and power system stability. Successful candidates should have a PhD in electrical engineering or a
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. Supervising student projects and theses, particularly within converter technologies, electrolysis integration, and power system stability. Successful candidates should have a PhD in electrical engineering or a
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Computational Linguistics, Computer Science, or a related field (e.g., Cognitive Science), with specialization in NLP, Machine Learning, or a similar area. Experience and interest in leading largescale open