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looking for postdoctoral researchers in the area of computer vision, AI, and machine learning. The initial appointment will be for 2 years with a possible extension with a tentative start date in January
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readings, qualitative empirical studies, etc.) that give equal attention to humans and nonhumans. Where to apply Website https://karriere.plus.ac.at/en/jobs/6fae92a6-fee4-4dcb-034e-691b1c67aa63/apply
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-fellow-in-deep-learning-for-subsurface-imaging Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290391/postdoctoral-research-fel… Requirements Research FieldComputer scienceEducation
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Ref.: 533588 Work type: Full-time Department: Teaching and Learning Innovation Centre (47500) Categories: Senior Research Staff & Post-doctoral Fellow, Research Staff Post-doctoral Fellow/Senior
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 25 days ago
the machine learning community as challenging, high-dimensional testbeds. Notably, the recently developed WOFOSTGym simulator \cite{solow2025wofostgym}, bridging crop modeling and RL, received the Outstanding
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, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology. Achieving
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on intelligent observing systems using machine learning and data assimilation methods in the ACTIVATE project. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/289326
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adaptive robotic strategies. The work will involve the integration of: Advanced motion planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow. We welcome you to join our community
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will contribute to developing know-how that can be used to generate a methodology based on physics-informed machine learning models for process development and optimisation. The project will validate a