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-of-the-art econometric methods such as staggered difference-in-differences, regression discontinuity designs, and causal forest–based identification strategies. We ask applicants to briefly sketch in
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You will focus on: Studying the slug stability of organic solvent slugs (e.g. acetone, acetonitrile, chloroform) in different push solvents for detection of apolar metabolites with segmented flow NMR
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-driven society—and who gets left behind? What are the rules that govern the development and deployment of Generative AI different sectors of society, and towards what kind of society will they steer us? Is
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(for example instruments control) You have proven experience in Python development You have experience in software development and validation, especially complex simulation software Ideally, you have direct
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will evaluate potential biases among different measurement approaches —including thermochronology, cosmogenic nuclides, and suspended sediment records— and apply advanced statistical analyses and erosion
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interest in learning, adaptation, and dynamical systems in physical contexts Experience with analytical and\or computational modeling. Proficiency in numerical methods and coding (Python, JAX, MATLAB
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of different types of populations. Work closely together with a PhD candidate on the same project and provide help with setting up simulations. Investigate the trend in genetic variance and genetic correlations
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and proficiency in Python (preferred) and/or MATLAB for data analysis are required. Experience with the assessment of masonry structures under multiple loading hazards. Language: Excellent command
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approaches treat NP design as static property prediction. This project takes a fundamentally different approach: using generative models to propose novel NP formulations and coupling them with explainability
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and digitizing archival data, strong knowledge of causal inference methods, good command of R and Python. Knowledge of machine learning methods is an asset. Strong command of English; command of either