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Field
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forcing of structural vibrations, often linked to the presence of complex flow features such as wakes and flow separation and their interaction, whose numerical representation can be challenging for legacy
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revealed with mechanistic predictors using advanced statistical and laboratory approaches. Responsibilities Plan, design and execute complex research studies, procedures and protocols in accordance with
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econometric modeling, scientific-oriented thinking, communication and team skills, with a PhD in the field of economics, (business) mathematics, (business) informatics, marketing, management. As a member of the
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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Data Assimilation, ESG Analysis, and Complex Network Theory for the Preservation of Global Commons” (Sub Project Leader: Tetsuo Hatsuda, Director of Division of Applied Mathematical Science) within
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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metagenomic data from soil microbiomes Bioinformatic analysis of soil metatranscriptomes Genome-scale metabolic modelling of complex communities Contribute to design and supervision of laboratory-based soil
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satisfactory performance and funding availability. Applicants should possess a PhD degree in epidemiology, biostatistics, applied mathematics, data science or other related disciplines. They should have strong
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infectious disease data using statistical and/or mathematical approaches would be highly desirable. Experience in statistical analysis, and proficiency in statistical and computer modelling software (e.g. R
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for Biosystems and Biotech Data Science is to pursue the development of new mathematical and computational approaches for complexity reduction of biosystems and for extracting knowledge from (vast) sets of biotech