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Project title: Developing and Evaluating Interpretable Approaches for Human-Centered Machine Learning.Project description: Approaches in interpretable machine learning offer promise in understanding
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tools such as LTSpice (preferred)/TINA/Multisim. Knowledge of low-power biopotential amplifier design and energy harvesting techniques is preferred. Candidates with machine learning skills, particularly
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Invitation to expressions of interest in PhD and Postdoctoral candidates interested in applications in the field Resilience and Risk of Critical Infrastructure. These roles focus on advancing methodologies, modeling, and technologies to enhance infrastructure resilience against emerging threats,...
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or equivalent) Experience with machine learning tools (e.g., Scikit-learn, Tensorflow, PyTorch, etc.) Track record of publications/and conference papers in software modelling or programming, or system level
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into University of Galway’s community. Living allowance (Stipend): €25,000 per annum [tax-exempt scholarship award]. Computer equipment and funding for travel (e.g. to conferences) as well as attendance
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fence-building, policing, military presence, infrastructure-development and domestic policies relating to citizenship and national security. The research will contribute to debates on migration, security
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focus on the Union’s potential to regulate the use of AI and to protect EU digital sovereignty. Existing scholarship on the military applications of artificial intelligence focuses either on global-level
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examining the key personal, educational, professional and systemic influences that define and shape their early careers and practice, including the impact of different learning and professional development
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capacity to learn technical skills, then perform the same tasks independently, reproducibly • Evidence of highly detailed, accurate record keeping • Excellent time management, written and
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Psychology at Trinity College. They will participate fully in lab life, attending regular meetings and collaborating with other lab members. They are expected to be a self-starter, eager to learn and