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methods for differential equations and scientific machine learning; geometric deep learning, manifold learning, equivariant methods, high-dimensional geometry, and structure-aware learning; and the
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of cryptographic implementations and hardware-security countermeasures. Experience with hardware reverse engineering, debugging interfaces, or firmware analysis. Experience with machine learning, deep learning
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/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is
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, Econometrics, and Equilibrium, Expectations & Dynamics (CeNDEF). Find more information … Where to apply Website https://www.academictransfer.com/en/jobs/363541/phd-candidate-in-aidriven-flood… Requirements
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and inclusive workplace. To learn more about our culture and hiring process, explore our Candidate Resource Hub . Where to apply Website https://www.timeshighereducation.com/unijobs/listing/415430
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: A doctorate in a Machine-Learning related field A deep knowledge of Control Theory, both classical and deep learning based A solid publication record in top level ML venues such as NeurIPs, ICML, and
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Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Oct 2026 - 00:00 (Europe/Brussels) Country Germany Type of Contract Temporary Job Status Part-time Is the job
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-facing web GIS dashboard. Investigate the forest, landscape, and climate conditions that drive storm susceptibility, using major windstorms as natural experiments and interpretable machine-/deep-learning
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program. Analyze and interpret remote sensing datasets (satellite, UAV, and/or LiDAR-derived) relevant to fire, fuels, and landscape-scale research questions. Develop and/or adapt machine learning and deep
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Apply Now How to Apply Applicants are required to submit their applications electronically by visiting https://apply.interfolio.com/191044 and uploading the following: cover letter curriculum vitae