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Field
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. The successful candidate will develop advanced machine learning (ML) models to automate and optimize retrosynthetic analysis, facilitating the discovery of efficient and sustainable synthetic routes for complex
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publications) • Experience with numerical simulations and/or geochemical modelling software • Advanced knowledge of isotope geochemistry and/or related field • High proficiency in English (C2 equivalence, both
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under realistic process conditions. Perform process simulations and scale-up assessments. Use advanced characterization techniques (XRD, BET, SEM, TPR, GC-MS, etc.). Collaborate with interdisciplinary
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indirect costs of urbanization. Calibrate this model using real data from specific case studies. Simulate urbanization costs based on various climatic, morphological, and social scenarios. Formulate
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these changes, identify their causes and describe their impacts on biodiversity and ecosystem services. To do this we use a combination of diverse methods, from empirical research to remote sensing and simulation
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-treatment, operational modes, and gas variability on final CO2 purity and process stability. Collaborate with process modelers and experimentalists to align capture conditions with system design and operation