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: Development of machine learning algorithms for the localisation of seismic sources (e.g., on 2D grid maps) Analysis and preprocessing of large DAS datasets Use of synthetic training data from seismic
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 9 days ago
machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern thinking, connecting decades of computer science methodologies with modern data and
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
/Qualifications Strong proficiency in at least one of these domains: astrophysics, data science (statistics, inference, and machine learning), or physical remote sensing/Earth observation. Strong skills in
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to machine learning. This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You
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, cell biology, time-lapse microscopy and single cell analysis. You will work in a dynamic and highly interdisciplinary team including computer scientists, experimentalists and clinicians. You will be
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; Distributed multi-agent sensing and cooperative positioning algorithms; Machine learning and data-driven methods for ambient awareness. Working Environment: The PhD will be conducted at the University
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partners. The postdoctoral researcher will also contribute to teaching in areas such as Machine Learning, NLP, AI for Education, Explainable AI, and Python-based applied seminars, supporting course
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and colleagues. Job Requirements: Required Qualifications: PhD in Human Computer Interaction, Computer Science or a related field by time of appointment Documented teaching and research ability
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sheet evolution, methane hydrate fluxes, or applying machine learning to geosciences to reconstruct glacial histories and project future ice sheet behavior. Please read this interview for more details
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software engineering, computer science, data science, bioengineering, bioinformatics, engineering, physics or related Experience in either machine learning or computational biology. Interest in both