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known for its high-impact research, aimed at solving problems across the globe. Interdisciplinarity, experiential learning, and connection to partners beyond academia are at the heart of the Northeastern
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to provide support for DH scholars around your area of expertise. You will be welcome to teach (optionally, for an additional fee). We particularly seek candidates with an interest in interdisciplinary work
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optimization methods for run-time network configuration and control. You will design efficient and lightweight learning-based techniques for automated scheduling, network resource allocation, and parameter
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related field and have previous academic experience in machine learning. The candidate should have a strong background in metrology and medical image processing. Active participation and collaboration
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for Evidence-Based Healthcare – a JBI Affiliated Group and is recognized as a WHO Collaborating Center for Evidence-based Medicine, and as a Center for Evidence Reviews of the American College of Physicians
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plasticity platform. Different machine learning strategies will be explored to capture the complex relationships between microstructural features and mechanical responses. In particular, the project will
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of material behavior to the development of the material to the finished component. PhD position on physics-based machine learning modeling for materials and process design Reference code: 980 - 2026/WD 1
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will also collaborate with a postdoctoral researcher and another PhD candidate on creating new GPU-enabled pharmacophore searching algorithms. Prospective validation will be achieved by predicting
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to work on cutting-edge research at the intersection of deep learning and computer systems. The successful candidate will join an international and collaborative research environment and contribute
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communities concerned? This research involves close collaboration with social partners such as the HERStory Art Foundation (Farida Nabibaks), Theater Thalia, and NAKS. As a PhD candidate, you will conduct