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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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aircraft are closely monitored to see if a soot-CCM effect can be predicted. What you would be doing: You will acquire in-situ and remote-sensing data of cirrus forming downwind of flights over the past
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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effect can be predicted. You will acquire in-situ and remote-sensing data of cirrus forming downwind of flights over the past decade, along with measurements/estimates of local conditions and emissions
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predicts the interactions of the evidentials with different types of speech act and syntactic contexts. The position begins on October 1, 2025 (or shortly after) and will run until June 30, 2029. The ideal
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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microbial communities. In this role, you will develop hybrid species distribution models that combine climate and landscape data to predict how microbial taxa niches shift under changing land use and
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will develop and apply cutting-edge methods in predictive and causal modeling for age-related macular degeneration (AMD), a primary cause of irreversible vision loss worldwide. This work will involve
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models. This theoretical project will facilitate close collaboration with experimental groups and enable benchmarking of theoretical predictions. The PhD researcher will be part of the Correlated Quantum
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Management and Analysis: Compile and analyze experimental data, comparing results with theoretical predictions to assess data quality. Technical Documentation: Prepare detailed reports and contribute