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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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Operations Research Economics 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
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Academies of Science Engineering and Medicine Workshops. Selected candidates will have the opportunity to train for publishing in leading biomedical journals and machine learning conferences, networking with
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strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 5 hours ago
, machine learning and data analytics, multi-objective optimization, life cycle assessment (LCA), serious gaming, and other participatory research methodologies. Candidates should also demonstrate leadership
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capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
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. Preferred qualifications: D. in Quantitative Genetics/Genomics, Computational Biology, or Related Discipline. Skilled in single-cell transcriptomic analyses, machine learning and artificial intelligence
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Decision Intelligence for Supply Chain and Operations Optimization. The successful candidate will contribute to cutting-edge research at the intersection of Statistical Machine Learning and Generative
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interdisciplinary and experiential learning to join the Source Project, Binghamton University's distinctive first-year research program in the Humanities and Social Sciences. The position begins August, 2025. PhD in
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experiments. Data & Analysis: • Collaborate with data scientists to analyze host and microbial data using statistical, bioinformatic, or machine learning approaches. • Contribute to the integration of spatial