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simulation models of existing test structure geometries to enable simulation and optimization for specific PIC platforms Investigate methods to optimize test structure designs for more robust determination of
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path to improved human well-being and flourishing, and not catastrophe? Existing approaches to alignment, such as RLHF, constitutional AI and social choice methods, focus on eliciting human preferences
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machine learning models with respect to accuracy and uncertainty quantification. - Developing software to implement the goals stated above (most likely in Python). - Disseminating results
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in experiments or fieldwork. Organize and manage research data, including data entry, coding, and maintaining data integrity. Use relevant software tools and methods as required. Assist in conducting
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models, frameworks, and methods to confront complexity underlying persistent societal challenges affecting the well-being of people and the planet. This position represents a unique opportunity to
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: A PhD degree in business, computer science, informatics, social sciences (preferably sociology, psychology, or economics), public health or a related field is required and must be conferred by
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: Doctoral-level degree in bioethics, philosophy, public health, law, medicine, social science, history or other relevant discipline, with fewer than five years of post-PhD research by the start date
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software to implement the goals stated above (most likely in Python). § Disseminating results through posters/seminars and international meetings and meeting seminars. § Ensuring that all results
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of advanced packaging reliability and provide a scientific basis for test method development, material selection, and product quality assurance for the semiconductor industry. Key responsibilities will include
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research initiatives that analyze the impact of AI technologies on social systems and design innovative methods for adapting economic and social governance to AI development. A special focus will be