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on the part of the assessment that concerns him/her self. Formalities and salary range Natural Sciences refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under
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data and deep learning methods to assess canopy cover, quality, carbon stocks, and ecosystem services. Mandatory requirements: PhD in areas related to forest resources, remote sensing, data science, or
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The Zhi Laboratory at Yale University (Department of Biomedical Informatics and Data Science) is seeking a highly motivated bioinformatician or computational biologist (Ph.D.) to join a method
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between the archaeological (AMGC) and AI (FLAIR) teams, contributing to the development of a simulator of real-world archaeological search processes and to the AI methods that learn effective discovery
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in vitro methods for the study of ticks and tick-borne pathogens. The project focuses on the development of artificial tick feeding systems, novel screening approaches for the identification
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control theory. Proficiency in theoretical modeling tools (e.g., effective Hamiltonians, master equations, feedback methods). Ability to work in a team and interact effectively with experimentalists
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possess a Ph.D. degree in Social Work, Psychology, Statistics, Public Health, or a related discipline. They should have sound knowledge of quantitative research methods and a good command of written English
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on the ultra-stable laser stations of the REFIMEVE infrastructure. The research will focus on developing experimental methods to exploit REFIMEVE's photonic and metrological systems for innovative measurement
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populations. Apply Artificial Intelligence (AI) methods including deep learning (DL) models and supervised and unsupervised machine learning (ML) methods for integration and for Genome-2-Phenome (G2P) and risk
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preparation methods, analytical analysis, experiments, analyzing chemical datasets, and synthesizing results to advance project objectives. Work will directly contribute to publications, project reports, and