7 machine-learning PhD positions in Italy

FAIROmics - PhD fellowship in Network-based algorithms for Knowledge Graph construction and analysis and application to the Omnicrobe knowledge graph.

candidate.Research field: Applied Physics, Computer Science, Data Analysis, Machine Learning, Artificial Intelligence.Type of contract: Temporary.Job status: Full-time.Duration: 36 months.Application deadline: 15/05

PhD position “Data-driven optimization for the manufacturing of multi-functional natural-based conductive hydrogels for flexible technologies applications”

strong background in the areas of materials science, mechanical engineering and machine learning, are welcomed The successful candidate will be part of a vibrant multidisciplinary and international group

FAIROmics - PhD fellowship in Artificial Intelligence-based tools for information retrieval from text documents - Automatic information extraction from scientific publications and other sources to build knowledge graph.

other sources to build knowledge graph.Researcher profile: Doctoral candidate.Research field: Applied Physics, Computer Science, Data Analysis, Machine Learning, Artificial Intelligence.Type of contract

PhD position on artificial muscles for soft robots - Department of Industrial Engineering (DII), University of Trento

, electronics, systems engineering, machine learning. A track record of project works Strong interest towards problem solving and experimental activity Fluency in English (written and spoken) Preferred

1 PhD position in Marie Slodowskwa-Curie Doctoral Network “NESTOR - Next generation high-speed optical networks for metro access”; research topic: “DC6: AI-based power saving and distributed sensing/failure prevention from optical telemetry”

by NESTOR is the combination of the advanced coherent pluggable transceivers with newly developed artificial intelligence/machine learning (AI/ML) algorithms, to allow the optical network to be

PhD position in Marie Slodowskwa-Curie Doctoral Network “NESTOR - Next generation high-speed optical networks for metro access”; research topic: “DC4: Digital twin of physical layer for short-reach scenarios in metro/access/DCI networks”

by NESTOR is the combination of the advanced coherent pluggable transceivers with newly developed artificial intelligence/machine learning (AI/ML) algorithms, to allow the optical network to be

A Researcher on Hydrogen Techno Economic Assessment

the definition of learning cost curves. Collaborate and coordinate activities on Tecno Economics Assessment Participate and collaborate with the engineering team to validate cost and technical model. Gathering