527 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" PhD positions
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will be made for all categories of stakeholders to support the process of job matching. Where to apply Website https://resurseumane.ase.ro/pnrr-cf_178-jobkg-a-knowledge-graph-of-the-romanian
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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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to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
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Interaction venues. For further information about the project, see: https://www.nordforsk.org/projects/nordic-perspectives-collaborative-ai-blue-collar-work-cai-blue. Your competencies You must hold a master’s
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-phd-positions/ . Requirements Top-ranked Master's degree in robotics, computer vision, system control, machine learning, mathematics, or a related field (background in any of the following); Being
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artificial intelligence, computer science, engineering, mathematics, physics, or a related discipline Demonstratable background in machine learning, information retrieval or natural language processing
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 29 days ago
the Medical University of Vienna, the Technical University of Vienna and University of Vienna, the AITHYRA and CeMM PhD programs for both life scientists and computational scientists/machine learning experts
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Experience and practical knowledge of programming languages and tools (e.g. Python, Java, etc.) Knowledge in Software Engineering, AI, machine learning is an advantage Experience with software observability
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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, water quality and meteorological datasets routinely collected by water utilities. The student will have the opportunity of using state-of-the-art machine learning methods (predictive analytics) to analyse