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of future wireless communication systems. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G networks, we use tools such as artificial intelligence/machine learning, quantum computing
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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Science Research unit: https://genomics.iit.it/ ESSENTIAL REQUIREMENTS PhD in computational biology, machine learning, bioinformatics, physics or related fields; High proficiency level in programming
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an enthusiastic and highly motivated researcher. You have, or will shortly, acquire a PhD degree in the field of Human-Computer Interaction, Interaction Design or Interaction Technology or equivalent Ideally, you
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techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
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traffic flow theory with machine learning, and with that, the best of both worlds: theory and logic where necessary, data-driven where possible. This innovative new approach enables more efficient and
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design. Perform large-scale computational screening using first-principles calculations and machine-learning potentials. Analyze structure–property relationships and extract scientific insights from AI
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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related discipline, with a focus on security, privacy, or applied machine learning, and with less than 5 years post receipt of PhD. Demonstrated research experience in at least one of the lab’s research
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Integration group led by Dr. Jędrzej Szymański. Our group specializes in machine learning, multi-omics data integration, and the development of predictive models for plant gene regulation. We are part of