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Field
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data and deep learning methods to assess canopy cover, quality, carbon stocks, and ecosystem services. Mandatory requirements: PhD in areas related to forest resources, remote sensing, data science, or
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design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale microbiome and genome
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the Italian Multiple Sclerosis Foundation (AISM/FISM), involving Dr. Raffaella Tonini (Neuromodulation of Cortical and Subcortical Circuits), Dr. Arash Ajoudani (Human-Robot Interfaces and Interaction), Dr
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employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the
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and motivated PhD student to contribute to the development of the next generation of DNA computers, capable of processing large molecular databases. The project will combine concepts from molecular
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interfaces. Plan controlled ablation studies and reproducible evaluations using scratch training across multiple seeds, exact train and validation metrics, parity and error analyses, gradient checks, and end
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within a multidisciplinary environment at the interface of biomaterials, cell therapy, pharmaceutical sciences and medical device development, contributing to the generation of proof-of-concept data
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multidisciplinary group at the crossroads of engineering and biology. Our research explores materials, technology and integration of soft bioelectronic interfaces and electronic skins. We design, fabricate and
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-solid interface. To connect materials to devices, you will prototype booster-bed reactors from mL to L scale by 3D printing and support the transfer of promising formulations toward scalable, solvent-free
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and polymer–fibre interfaces. Manufacturing and processing of composite materials using appropriate techniques. Mechanical, thermal, thermo-mechanical and physicochemical characterization. Investigation