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candidates will be involved in a project that is related to 3D Content Generation. The key responsibilities include the following: To independently undertake research in computer graphics and machine learning
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in a research project on machine learning modeling and optimization of vertical farms. Key Responsibilities: Development of new machine learning modelling approaches Development of new advanced control
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writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning and optimization & controls Having basic knowledge in carbon
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: Master degree in Computer Science/Engineering or equivalence More than 5 papers published at top AI/Machine learning conferences Experience of deep learning and machine learning Good communication and
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or equivalent. • Have relevant research/industry experience in Machine Learning, AI and Privacy. • An excellent team player who can cope with an agile and fast-paced environment. • Good communication
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Responsibilities: Conduct programming and software development for big data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations
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science, machine learning, artificial intelligence, or a related field. Candidates with a PhD may be considered for a Research Fellow position instead. Prior experience with video data visualization research will be
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, reinforcement learning, AI agents, and machine learning. Job Description Conduct research in the field of neural networks, natural language processing (NLP), and large language models (LLMs). Independently read
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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, JSON, NIfTI, BIDS). Build and deploy scalable, containerized Docker/Singularity workflows using NiPreps tools (fMRIPrep, sMRIPrep, MRIQC etc.). Explore and apply machine learning models (e.g., Nilearn