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PhD Research Fellow in statistical population ecology is available at Department of Biosciences, University of Oslo (UiO), within the Convergence Environment ’Methods for knowledge-based biodiversity
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qualifications: A strong background in algebraic topology. Experience in any of the following: Higher category theory, stable homotopy theory, simplicial methods. An interest in computer algebra and programming
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cooperation with the Institute of Marine Research. The core of the position will be on development of new deep learning methods for segmentation/classification of data with limited and weak labels. Your may
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methods will be advantageous: Microbiological techniques, as well as computer-based analysis Molecular biology techniques Analysis of high-throughput datasets (DNA seq, microbiological data, competitive
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micrometeorological and remotely sensed datasets, as well as the analysis of soil and plant samples. Advance experimental design techniques by developing, evaluating, and refining innovative measurement methods
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approaches to fabrication prediction, structural and material optimisation, computer vision for process monitoring and quality assessment, and the integration of machine learning methods within design
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, stable homotopy theory, computer algebra. All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based
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, or similar systems) Experience or strong interest in: Benchmarking and evaluation of complex AI systemsm Robustness, uncertainty estimation, and failure-mode analysis, Deployment of AI systems in high-stakes
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throughout the doctoral education. Research topic This PhD project addresses a critical challenge in structural integrity assessment: the lack of reliable non-destructive testing (NDT) methods capable
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humanities studies of sustainability, Norway, China and food systems. Applicants must have experience with mapping and programming methods in architecture and urban design, particularly in site analysis