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Strong quantitative skills and experience with scientometric methods, machine learning for text analysis, and possibly LLMs. Experience with the analysis of science and technology data (patents and
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-of-the-art in SLAM, situational awareness, computer vision, machine learning, robotics, and related fields Developing and implementing innovative solutions, validated through real datasets and experiments
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human
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the development of hierarchical computational materials discovery schemes combining random structure searching, machine learning, atomistic, and density functional theory (DFT) calculations to accurately and
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD (or foreign equivalent) in Physics, Electrical Engineering, Material Science or closely related field in hand
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through soft, disordered materials, including auto-regulated networks, composite soft solids, and exotic photonic biomaterials. The lab has two fully funded PhD and/or postdoctoral positions available
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Centrum Wiskunde & Informatica (CWI) has a vacancy in the Machine Learning research group for a talented Postdoc/researcher (m/f/x). Job description We are looking for a motivated postdoctoral
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Institute faculty, in areas such as: * Machine Learning and Computer Vision * Natural Language Processing and Data Science * Biomedical Informatics and Computational Neuroscience * Mathematical/Theoretical
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying