COMPETITION FORRESEARCH CONTRACT, GROUP 02/PTHEORETICAL PHYSICS OF FUNDAMENTAL INTERACTI
Organisation/Company Bocconi University Research Field Computer science Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 8 Nov 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 project aims to develop and validate learning rules that are local in space and time for recurrent neural networks, based on the geometry of stable states and compatible with low-power neuromorphic processors. Activities include theoretical analysis for continuous and finite-precision units, convergence analysis, assessment of scalability and performance in online,
continual and few-shot learning, quantization of weights and activations, and validation on emulators and physical hardware. Accuracy, energy consumption and memory usage will be measured. In collaboration with the Principal Investigator and other collaborators, the researcher will develop and implement algorithms, conduct and document experiments, analyse results and compare them with the state of the art. The researcher will also adapt the algorithms to hardware constraints and prepare the release of documented, reproducible open-source software.
Italy
Eligibility of fellows: country/ies of residence:
EUROPE
Eligibility of fellows: nationality/ies:
#J-18808-Ljbffr
Offer Description The project aims to develop and validate learning rules that are local in space and time for recurrent neural networks, based on the geometry of stable states and compatible with low-power neuromorphic processors. Activities include theoretical analysis for continuous and finite-precision units, convergence analysis, assessment of scalability and performance in online,
continual and few-shot learning, quantization of weights and activations, and validation on emulators and physical hardware. Accuracy, energy consumption and memory usage will be measured. In collaboration with the Principal Investigator and other collaborators, the researcher will develop and implement algorithms, conduct and document experiments, analyse results and compare them with the state of the art. The researcher will also adapt the algorithms to hardware constraints and prepare the release of documented, reproducible open-source software.
Italy
Eligibility of fellows: country/ies of residence:
EUROPE
Eligibility of fellows: nationality/ies:
#J-18808-Ljbffr