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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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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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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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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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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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processing, or spectroscopy. Familiarity with hyperspectral imaging or related optical imaging methods is an advantage. Strong programming skills in Python and/or MATLAB. Interest in applying machine learning
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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
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are looking for a candidate with a track record within observational research and with experience with machine learning or other relevant data science techniques. The scientific background
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of the following areas: Research and development within computer vision and machine learning. Research and development within UAS platforms, subsystems, and payloads. Software design and development (C, C++, Python
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at CPPEM (see more below). We are looking for a candidate with a track record within observational research and with experience with machine learning or other relevant data science techniques. The scientific