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. Responsibilities: • Design and conduct experimental research on paper-based materials for food packaging applications. • Develop predictive models for packaging performance using machine learning and physicochemical
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with rich clinical data. Advanced modeling of arrhythmias using generalized linear models and machine learning. Helps in training and mentoring of lab personnel, including graduate and undergraduate
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of Engineering Science. The post is funded by EPSRC and is fixed term to the 31st January 2027. A2I explores core challenges in AI and machine learning to enable robots to robustly and effectively operate in complex, real
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or recent Ph.D. in applied/computational mathematics, computational science, chemical engineering, or related disciplines. Ideal candidates will have strong past experience in scientific machine learning
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to joint research activities, publications, and surveys. Requirements PhD degree (or near completion) in robotics, control, machine learning, or a related field; Strong publication record demonstrating
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 7 hours ago
software development experience. PREFERRED: Experience with rotational spectroscopy, radio astronomy, radiative transfer calculations, and/or machine learning. These qualifications can be demonstrated
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analysis to translate THz signals into optical material properties such as refractive index and absorption coefficient. Development of machine learning algorithms for material classification. Exploration
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systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine first-principles modeling, machine-learning
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that currently lack effective treatments, such as Parkinsons Disease. By combining machine learning with quantum chemistry and structure based approaches, the project will accelerate the translation
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. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in time and space, how this affects