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Field
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Dust Analyser onboard the Cassini space probe - Collaboration with a computer scientist who is developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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at New York University Abu Dhabi seeks to recruit a motivated post-doctoral associate with a strong background in game theory, control systems, and/or learning theory to join the research team of Prof
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, operations research, and management science, developing rigorous and practical methods for algorithmic risk assessment. You will become part of the broader AI2 collaboration, involving leading researchers from
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consists of three major parts: sensor printing, circuit design and integration and developing of an AI algorithm and using it to teach the sensor to selectively measure desired gases . In this role, you will
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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design, development, and validation of material, control systems, and algorithms for next-generation soft haptic actuators and experiences. Note that the research involves significant interactions with
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entails the development of heuristic and metaheuristic algorithms, as well as GIS map integration, for the most effective management and suppression of wildfires. You will work in an international team
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Your Job: Developing and implementing QC algorithms (QAA, QAOA, QSVM), quantum AI algorithms, use case adapted algorithms to test and benchmark latest technology focusing on gate-based QC Advancing
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analysis, data modeling, and algorithm development. Experience with environmental analysis or microplastic research is a plus but not required. Strong analytical and problem-solving skills, ability