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Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F This post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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22.10.2020, Wissenschaftliches Personal PhD and PostDoc Positions in Visual Computing & Artificial Intelligence: we are looking for highly-motivated PhD students and PostDocs at the intersection
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Discipline: Process Mineralogy, Mineral Processing, Artificial Intelligence Duration: 12 months, with the possibility of renewal for an additional 12 months Institutions: UM6P-Benguerir/ Mineral-X
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young people, their families, and educators to develop a neurodiversity-affirming toolkit to explore children’s character strengths, abilities, and potential across contexts. Embedding Artificial
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Postdoctoral Researcher: Oxford Centre for Emerging Minds Research ‘All About Me’ (Adolescent Focus)
Artificial Intelligence and assistive technology, we aim to be at the forefront of equipping key stakeholders to identify, explore, and scaffold opportunities for strengths-based approaches that allow
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Artificial Intelligence (AI), particularly in the development and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have
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models Experience in artificial intelligence to develop the algorithms for digital twins Experience with both qualitative and quantitative data analysis techniques Experience in cleaning and analyzing
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Postdoctoral Associate Required Qualification: (as evidenced by an attached resume) PhD (or foreign equivalent) in Bioengineering, Genetics, Genomics, Biomedical Engineering, Analytical Chemistry
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI