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Postdoctoral Research Fellow (tenure track) automation of operations/analyses in chemical synthesis Apply for this job See advertisement UiB - Knowledge that shapes society Through robust and close
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of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees. You will be will working within the Center
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of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees. You will be will working within the Center
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.) and to infer which genome-encoded functions are actively expressed under different biofloc maintenance and aquaculture practices, enabling data-driven strategies to steer floc composition. Expected
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the application of rock physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or
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including, high resolution 3D and 2D seismic, sub-bottom profiler, regional 2D seismic and petrophysical logs; infer complex Earth system process understanding, including changes in current patterns, glacial
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of past warm periods in diverse geophysical datasets including, high resolution 3D and 2D seismic, sub-bottom profiler, regional 2D seismic and petrophysical logs; infer complex Earth system process
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will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning
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or more of the following empirical research methods will be considered an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the
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analyses, including demographic inference, selection scans, and gene-environment and gene-phenotype association studies. • Plan and conduct fieldwork to collect plant material across Arctic locations, and