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career scientist with background in organic geochemistry, statistics, and Bayesian modeling to pursue analyses of paleoclimate biomarker data. The ideal candidate should be proficient with both laboratory
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communication and collaboration skills Preferred: Experience with simulation-based inference and Bayesian methods Familiarity with cosmological simulations or observational cosmology ML architecture design and
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, hydro-acoustics, data science, geodynamics, geophysics, statistics, Bayesian inference ⁃ Experience with statistical analyses and machine learning techniques ⁃ Programming in C / python / Julia
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diagnosis of psychosis. The postdoctoral researcher will lead a research program focused on developing and testing the computational mechanisms of social inference, although will have plenty of scope, and
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., Merilä, P., Vanhatalo, J. & Laine, A.-L. (2024) Inferring ecological selection from multidimensional community trait distributions along environmental gradients. Ecology, 105(9): e4378. Doi: doi.org
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. Ecology Letters, 28(4): e70003. Doi: 10.1111/ele.70003 Kaarlejärvi, E., Itter, M. S., Tonteri, T., Hamberg, L., Salemaa, M., Merilä, P., Vanhatalo, J. & Laine, A.-L. (2024) Inferring ecological selection
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experimental methods. Develop and apply methods for demultiplexing, normalization/QC, effect-size estimation, biological inference, and predictive modeling. Contribute to biological manuscripts and methods
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techniques from statistical physics, Bayesian inference, and complex systems theory to address challenges posed by noisy and incomplete data. Depending on the results obtained in the first year, the post can
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experiments. The objective is to develop Bayesian causal models and neural networks capable of identifying relevant causal relationships between instrumental parameters and observed anomalies. The work will
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developing and testing the computational mechanisms of social inference, although will have plenty of scope, and will be encouraged, to develop and expand their own research interests. The postholder will work