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to contribute to the development of innovative machine learning solutions using deep learning and multimodal foundation models. Working closely with leading researchers, you will design, develop, and implement
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direct MTRI’s machine learning (ML) research portfolio within a government-focused R&D environment. This role will shape our ML strategy, lead business development efforts, and serve as Principal
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About the role This project will develop new machine learning techniques to enable efficient production of bespoke products, such as medicines in a high-volume, high-variation manufacturing setting
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The aim is to develop machine-learning models that describe how
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application of advanced machine learning techniques, including deep learning approaches, aimed at identifying complex patterns of host immune responses to vaccination. The research activities will also include
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About the role This project will develop new machine learning techniques to enable efficient production of bespoke products, such as medicines in a high-volume, high-variation manufacturing setting
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Department of War security clearance. Knowledge, Skills, and Abilities: Deep Technical Knowledge: You have performed extensive research or engineering activities in applied machine learning and artificial
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Center for Emergence in the Molecular and Cellular Sciences (NCEMS) and the Institute for Computational and Data Sciences (ICDS) at Penn State seeks an outstanding scientist to fill a Machine Learning
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based on machine learning tools for energy problems related to prediction. The application domains include both industry and climate changes. The first two months will be devoted to the study of
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tools. Hands-on experience in autonomous robotics projects; exposure to deep learning or reinforcement learning is a plus. Strong problem-solving ability, collaborative and independent work style