1 Research contract - NeSy AI neurosymbolic LI/16456

Descripción

Offer Description: As part of the European CEREBRA-AI research project, which the successful candidate will join, the following tasks will be carried out: 1. Develop a hybrid neurosymbolic reasoning engine for verifiable multi-step inference. 2. Orchestrate continuous learning in agents that comprise specialist models, detect changes in model evolution, mitigate deviations and biases, and balance accuracy, latency and energy consumption. 3. Develop a cross-cutting framework for trustworthy AI for relational and interactive models embodied in agents, robots and digital twins, integrating explainability, traceability, bias auditing and compliance with the AI Act. Requirements: Research Field Other Education Level Bachelor Degree or equivalent Skills/Qualifications Bachelor’s Degree in Computer Engineering and Master’s Degree Specific Requirements Additional qualifications 20%: A degree in Computer Engineering and a complementary Master’s degree in a related field. Additional qualifications that will also be taken into account: 1. Complementary training in multidisciplinary qualifications and subjects related to the field. 2. Language qualifications. 3. Experience in international academic and industrial settings (e.g. experience in developing software applications and web infrastructure; ingestion, processing, harmonisation and integration of heterogeneous data; use of cloud infrastructures and deployment environments (GCP, AWS, Docker, version control with Git). Professional experience 20%: Research experience in the tasks to be carried out. Verifiable experience in the development of reliable, explainable, unbiased and verifiable deep learning AI models, in particular, neurosymbolic AI technologies such as the design, development and integration of knowledge graphs, graph neural networks and logic programming in workflows for reasoning models using general-purpose foundational models. Use of deep learning libraries: PyTorch. Experience publishing scientific papers at prestigious conferences on machine learning and AI. Other criteria 20%: Personal interview if applicable.

Sectores

Fuente

Fuente: euraxess.ec.europa.eu