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Field
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challenging, especially in dunes with complex topography. Your job In this 2-year postdoc position, you will use numerical modelling and machine learning techniques to increase the accuracy of coastal dune
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division and stabilization, and characterize frequency stability, phase noise, and timing jitter. Develop numerical models and experimental-control or data-analysis software where relevant. Collaborate
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. Experience with scientific programming, experimental automation, and data analysis using, for example, Python, MATLAB, or LabVIEW. Experience with numerical modelling of nonlinear or integrated photonic
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fluxes and acidification in global marine P cycling through a combination of field work in the North Atlantic Ocean, laboratory experiments and numerical modelling. A scientific cruise with our research
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political communication and public opinion Social and behavioral effects of generative AI Computational analysis of digital and scientific ecosystems Human-centered evaluation of AI systems Reproducible
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applicable. Preferred Qualifications PhD in data science, and/or public health or related fields including health services research, health informatics, computer science. Experience in data analysis using
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metabolomics gained during their PhD, covering the entire analytical workflow, from sample preparation to data analysis. A good understanding of plant metabolism is also desirable. Skills ➢ Qualifications
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experience with Linux is therefore also required • Candidates with a completed PhD degree before the interview date will also be considered • Documented research experience on numerical modelling
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improving the security of modern computer systems. To do that, we often build novel analysis techniques to uncover previously-unknown attack surfaces and when appropriate we design and implement new systems
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Austrian Academy of Sciences, The Institute for Habsburg and Balkan Studies (IHB) | Austria | 30 days ago
guidelines, co-supervising two student assistants Conduct in-depth historical and philological analysis of the Frangochiotika sources jointly with the PI Lead the project's micro-level analysis of vernacular