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learning video-AI models; b) assess representational alignment of bio-inspired deep learning models to the human brain. The bio-inspired models will be enriched with different temporal integration mechanisms
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root architecture and soil characteristics. Nominate and help evaluate promoter regions and candidate genes to enhance nitrogen use efficiency. Apply machine learning models to classify molecular
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critical maritime operation or system Collecting and curating operational and security-related data for AI-based threat analysis Training AI and machine learning models for anomaly and threat detection
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integrating modeling, machine learning (ML), and advanced control methodologies. The research will focus on designing AI-driven algorithms to assess battery health, predict degradation trends, and optimize
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 15 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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inference, and Machine Learning methods. In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group, as
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Infrastructure? No Offer Description Work group: IAS-8 - Datenanalyik und Maschinenlernen Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student in machine learning to work within
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models. The role also requires significant experience in classical machine learning methods such as decision trees, gradient boosting machines, and both shallow and deep learning networks. A demonstrated
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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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: genetics, epigenetics, inflammation, metabolic pathology, autoinflammatory pathology, autoimmunity, arthritis, computational analysis, mathematical modeling, applied algorithms, machine learning in biology