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data from textual sources Conduct data analysis using econometric and statistical tools (STATA, R, or Python). Assist in literature reviews and summarising academic research. Contribute to writing
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that generalize across different physical settings. Building on this motivation, the project focuses on the definition, development, and analysis of scientific foundation models: large-scale, generalizable models
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the analysis of large-scale omics data (e.g., proteomics, metabolomics, transcriptomics), including basic programming skills in R and/or Python Documented experience with exercise testing (e.g., testing
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are needed to prevent infections with bacterial enteropathogens and AMR. Our previous research showed that there are differences in the E coli colonization of infants’ microbiome between LMIC vs. high-income
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suspension pipe flow by 30–40% across different flow rates. This makes designing and controlling these flows difficult. The difficulty arises partly because these flows do not fit the conventional ‘laminar
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numerical experiments; programming experience in a language such as Python, Julia, MATLAB, C or C++; good written and spoken English; the ability to work independently while also collaborating in
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plasticity consists in learning dendritic, synaptic, or axonal temporal delays to enrich the network’s spatiotemporal dynamics. This research project will thus explore how these different mechanisms can be
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and/or Python; experience with Unix/Linux environments and bash is considered an advantage Prior experience in the preprocessing, analysis and interpretation of omics data and a strong interest in
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sector raise new questions and requires different and additional scenarios. There are gaps in the probability domain between normative events for water systems and stress tests events, and from an ESG and
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management questions; applications in the financial sector raise new questions and requires different and additional scenarios. There are gaps in the probability domain between normative events for water