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Field
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(supervisor) The position holder will be required to perform the following tasks/will do research on the following topics: Software engineering practices for machine learning Tabular machine learning Large
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an adaptable Machine Learning (ML) hardware architecture to solve Artificial Intelligence (AI) classification tasks using Internet of Things (IoT) sensor data. This will be a small system-on-chip designed
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 27 days ago
to gain exposure to and training in state-of-the-art uses of machine learning for solving complex optimization problems with realistic applicability in real-world investment settings. The position is ideal
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to early phase clinical trials. We collaborate with investigators intramurally (Duke Pharmacology & Cancer Biology, Cell Biology, Biomedical Engineering), and extramurally nationally and internationally
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(e.g., Computer Science, Software Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field) Strong skills in machine learning and deep learning Experience
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certification, dramatically accelerating innovation cycles. What you will gain: Expertise in Finite Element Analysis, Scientific Machine Learning, Uncertainty Quantification, and Professional Programming
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, please visit our website at www.cruk.cam.ac.uk/research-groups/aliee-group In the Aliee lab, we aim to address some fundamental questions in biomedicine through advancing machine learning. We develop
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applicants who have a background or strong interest in Computer Science, interactive media, software engineering, 3D modelling/animation, VR/AR, human–computer interaction or related digital-tech fields
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of students and can include, technique development, microscopy-spectroscopy, analysis/programming (including AI and machine learning) and materials-focused studies. We use innovative high-resolutionidentical
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develop methodologies (such as acoustic emission method) detecting early signs of damage, leaks, or degradation before they become critical. We will also leverage the latest developments in machine learning