Platforms, tools, and methodologies for modeling, design, and control of advance
Italian Ministry of Education, University and Research, Italy, NY, United States
Organisation/Company ALMA MATER STUDIORUM - UNIVERSIT e0 DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA DELL'ENERGIA ELETTRICA E DELL'INFORMAZIONE "GUGLIELMO MARCONI" Research Field Engineering bb Control engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 4 May 2026 - 23:59 (UTC) Country Italy Type of Contract To be defined Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description The activities of this research assignment will mainly involve:
Study and development of innovative control, actuation, and data acquisition platforms for mechatronic systems, based on embedded-edge architectures with possible cloud integration and advanced power electronics devices.
Advanced modeling and simulation for mechatronic, robotic, and automation systems, with semi-automated energy-consistent models and digital twins to generate reliable synthetic data.
Control and diagnostic techniques based on hybrid approaches integrating advanced control theory and AI-enabled methods.
The activity will be carried out within the ACTEMA research group (https://dei.unibo.it/en/research/research-groups/actema), in collaboration with other entities and groups, where necessary.
Eligibility country/ies of residence: All
nationality/ies: All
#J-18808-Ljbffr
Offer Description The activities of this research assignment will mainly involve:
Study and development of innovative control, actuation, and data acquisition platforms for mechatronic systems, based on embedded-edge architectures with possible cloud integration and advanced power electronics devices.
Advanced modeling and simulation for mechatronic, robotic, and automation systems, with semi-automated energy-consistent models and digital twins to generate reliable synthetic data.
Control and diagnostic techniques based on hybrid approaches integrating advanced control theory and AI-enabled methods.
The activity will be carried out within the ACTEMA research group (https://dei.unibo.it/en/research/research-groups/actema), in collaboration with other entities and groups, where necessary.
Eligibility country/ies of residence: All
nationality/ies: All
#J-18808-Ljbffr