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Research Infrastructure? No Offer Description The requested figure will be responsible for developing and implementing both machine-learning methods for analysing images and audio files in Python, as
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of signal processing and machine learning algorithms for the extraction of acoustic, prosodic, and semantic parameters from voice recordings. Alongside the innovative research activities, the project requires
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traditional and machine-learning and AI-based approaches will be used. Where to apply Website https://aunicalogin.polimi.it/aunicalogin/getservizio.xml?id_servizio=1079 Requirements Additional Information
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Description REALISE - Bridging Igneous Petrology and Machine Learning for Science and Society About the REALISE Doctoral Network REALISE will train 15 Doctoral Candidates at the interface of igneous petrology
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dependable large-scale software systems, integrating expertise in: Software Engineering Machine Learning & MLOps Robotics & Cyber-Physical Systems Cloud & HPC ecosystems Interdisciplinary research. As a
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experience in Artificial Intelligence (AI) and Machine Learning (ML) concepts, algorithms, and frameworks; Hands-on experience with popular ML libraries and tools (e.g., TensorFlow, PyTorch, scikit-learn
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, enabling innovative applications and translational research. We seek exceptional candidates with strong expertise in the fields of genome editing and cellular immunotherapy (CAR-T cells, NK-cells
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experience with EB-PBF systems is considered an asset) Python programming Statistical learning / machine learning / machine vision / Artificial Intelligence methods Image and signal processing (familiarity
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the next generation of secure agentic AI systems through cutting-edge research in adversarial machine learning and formal verification. The Role As a research scientist, you will contribute to frontier AI
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and development of perception stacks for autonomous mobile systems in general in any field Machine learning/deep learning experience applied to perception and any experience with deep Learning