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to establish a novel wireless plant-based communication system, using plants as natural antennas, uniquely powered by the integration of plant-microbial electricity generation seamlessly blended
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independent researcher in Ethics, Societal Impact, the Anthropology of emerging technologies and Strategic Science Communication, with proven experience in qualitative research, interdisciplinary collaboration
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of information technology and communication; Solid background and research experience in two or more of the following areas: AI techniques to secure networked computing infrastructures; Data science and statistical analysis
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system to monitor the overhead catenary" -the research activity consists of the design and validation in the laboratory and, subsequently, in the field, of the operation of a wireless and energy-autonomous
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intelligent robots. Developing adaptive learning and deployment frameworks enabling secure, trustworthy, and robust operation of AI models embedded in CPS. Conducting empirical and experimental studies at scale
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understanding of AI security. Collaborate with academic partners and the research community to advance the state-of-the-art in adversarial robustness and trustworthy AI systems. Minimum Qualifications PhD in
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, geneticists, and other colleagues in the Centre to develop and implement robust machine learning frameworks and pipelines focused on disease evolution prediction; Interpreting results and communicating findings
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collections and listening community". The successful candidate of the “Incarico di ricerca post doc” will join the Column research team of the COLUMN project aiming at investigating scientific colonialism and
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., Xarray, PyTorch/Scikit-learn). Methodology: Strong background in data classification and advanced Machine Learning. Soft Skills: Excellent communication skills, a collaborative mindset, and a desire to
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rendering, Gaussian splatting, etc.). Knowledge of graph neural networks. Experience in deploying and fine-tuning DL models, also large language or vision-language models. Practical experience on deploying ML