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Field
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leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis of normative frameworks and aggregation rules, and
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aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will support the development
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optimization algorithms for both estimation and inference. Special emphasis is placed on advancing statistical approaches to address the demands of increasingly complex, high-dimensional, and unconventional data
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computational social choice, and aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will
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and evaluation. The post holder will take a leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis
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: Beijing, Beijing, China [map ] Subject Areas: Physics / Condensed Matter Theory , Quantum Computation , Theoretical Physics Compensation: >300000RMB Appl Deadline: (posted 2024/12/09, listed until 2025/09
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positions listed below are limited availability positions. Please note that only students currently enrolled at Taubman College are eligible to apply to become a graduate student instructor (GSI) at Taubman
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, United States of America [map ] Appl Deadline: (posted 2025/06/24, listed until 2026/06/23) Position Description: Apply Position Description Overview Susquehanna is expanding the Machine Learning group and seeking
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: BEGIN Internship Location: Bala Cynwyd, Pennsylvania 19004, United States of America [map ] Appl Deadline: (posted 2025/06/24, listed until 2026/06/23) Internship Description: Apply Internship Description
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. The candidate will design algorithms that synchronize and fuse heterogeneous data sources to improve perception robustness under variable underwater conditions. Segmentation and classification: Training