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a multi-method and multi-stakeholder investigation to develop a comprehensive framework of the affordances, responsibilities, and outcomes of algorithmic decision-making, to help explore question
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a multi-method and multi-stakeholder investigation to develop a comprehensive framework of the affordances, responsibilities, and outcomes of algorithmic decision-making, to help explore question
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-stakeholder investigation to develop a comprehensive framework of the affordances, responsibilities, and outcomes of algorithmic decision-making, to help explore question of what explainable and accountable AI
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to the development and implementation of innovative algorithms for omics data analysis, including the integration of machine learning methods in bioinformatics. Where to apply Website https://www.umft.ro/ro/inginer-de
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or equivalent Skills/Qualifications Practical experience in Machine Learning and Computer Vision; Advanced knowledge of Python and C++ for developing efficient and high-performance algorithms; Experience with
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causal knowledge graph, prepare an operational algorithmic platform, answer and explain complex questions about the known and possibly unknown phenomena, address ethical and inequality protective issues
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deep learning algorithms by leveraging LLMs and compare them with traditional methods; and 4) develop a set of tools on the project's website that can be used to evaluate lexical complexity, readability
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also devise ML/AI instruments that model the causal effect of interventions/shocks on price developments and market outcomes. Beyond their merit for risk management, these new causal approaches also