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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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food production Food systems modeling We seek candidates with clear plans for research translation, including collaboration with in-Kingdom and international partners, and a pathway to validate and
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 16 hours ago
food production Food systems modeling We seek candidates with clear plans for research translation, including collaboration with in-Kingdom and international partners, and a pathway to validate and
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 16 hours ago
alternative-source production Resource recovery and waste valorization Water system modeling We seek candidates with clear plans for research translation, including collaboration with in-Kingdom and
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Vision, Video Understanding, and Multimodal AI. Design AI models for concept-driven video understanding of consumer facial care behaviours. Work with PI and company to develop the AI solution Develop novel
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. The project will combine experimental and clinical research to advance theory-driven treatment improvements. Your colleagues: You will work within a highly collaborative and interdisciplinary team across
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highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud
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of Chemical and Biological Engineering Posting Number R260133 Posting Link https://www.ubjobs.buffalo.edu/postings/64055 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment
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8 Jul 2026 Job Information Organisation/Company Saarland University Department Data Driven Simulation and Analysis in Material Science Research Field Computer science Researcher Profile Established
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natural language processing with causal estimation. Recent directions in the project include using large language models to remove treatment-predictive information from text, benchmarking debiasing