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Field
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willingness to explore new ideas and methods. Desirable Foundational knowledge of quantum computing, algorithms, and their applications. Understanding of software engineering principles, including compiler
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, algorithms, or computer science courses. Strong understanding of core data structures (e.g., arrays, linked lists, stacks, queues, trees, graphs, hash tables) and algorithms (e.g., sorting, searching, dynamic
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relevant area of mathematics or theoretical computer science. Demonstrated expert knowledge in asymptotic, algorithmic or probabilistic combinatorics, or a closely related area Demonstrated high level
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Susquehanna International Group, Quantitative Research Internship ID: SIG -QSTINT28 [#26690] Internship Title: Machine Learning Internship Program – PhD Hire – NY/Philadelphia area Internship Type
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EmoRoom (Emotion + Classroom), an interactive visual analytics system to analyze and summarize student emotions from classroom videos, using emotion recognition algorithms and intuitive visualizations
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advanced proficiency in the underlying science, math, statistics, data analysis, and algorithms of computational research questions at a level sufficient to converse with Princeton’s world-class researchers
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a basic knowledge of the donor medical requirements and contraindications. Accurately collects, records, and maintains clinical records of donors and recipients as required by the program in
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computational physics, machine learning, or related areas. Practical experience in developing novel AI/ML models and algorithms. Experience collaborating in multidisciplinary research environments. Strong oral
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at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design and evaluation. The post holder will take a
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leading researchers at NTU and publish in top-tier computer science conferences or journals. Key Responsibilities: Conduct research on vulnerabilities detection in 3GPP specifications via LLM. Develop