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reference features for machine learning (AI) algorithms. The successful candidate will work as part of a multidisciplinary team of archaeozoologists and mathematicians. The mission will be based at the CEPAM
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of the following tasks: Development of subsystems for high-speed optical communication systems, including pointing, acquisition and tracking, optical fiber coupling and digital signal processing (DSP) algorithms
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iteratively refine algorithms to ensure scalability, reproducibility, and biological interpretability. Behavioral Representation Learning and Temporal Modeling (30%) Build canonical behavioral embeddings
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to generate baseline datasets for calibrating and validating predictive models of biodiversity-rich forests. Using machine learning (ML) algorithms, the Research Assistant will help predict the occurrence
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 17 days ago
will develop computer vision, machine learning and control algorithms for a robot to perform packaging tasks. Human demonstrations will be used to generate data for learning. These data will encompass
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Scheduled Hours 40 Position Summary Performs innovative data analyses on neuroimaging and related data. Develop and implement computer algorithms for analyzing that data. Assume major responsibility
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programme Reference Number AE2025-0568 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0568
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of the discipline, industry and society. For further information about the School, please visit http://www.civeng.unsw.edu.au/ Skills & Experience PhD in a relevant discipline or equivalent experience. Demonstrated
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research in neuro-symbolic AI, with a focus on using generative and agentic AI, as well as AI standards to create trustworthy information resources. This includes the design of algorithms, tools, and process
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Your Job: Join our team as a dedicated scientist and contribute to our exciting research projects. Our work focuses on models and algorithms for supervised and unsupervised learning. We devise deep