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Extremadura, España UNIVERSIDAD DE GRANADA Jornada completa

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Organisation/Company UNIVERSIDAD DE GRANADA Department Vicerrectorado de Investigación Research Field Other Researcher Profile Established Researcher (R3) Positions PhD Positions Application Deadline 20 Oct 2026
- 23:59 (Europe/Madrid) Country Spain Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As part of the European CEREBRA-AI research project, which the successful candidate will join, the following tasks will be carried out:
* Develop a hybrid neurosymbolic reasoning engine for verifiable multi-step inference.
* Orchestrate continuous learning in agents that compose specialist models, detect changes in model evolution, mitigate deviations and biases, and balance accuracy, latency and energy consumption.
* 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. Additional qualifications (30 per cent) A degree in Computer Engineering and a complementary Master's degree in a related field. Ideally, a PhD in Computer Engineering or a related field. Additional qualifications that will also be taken into account:
* Complementary training in multidisciplinary qualifications and subjects related to the field.
* Language qualifications.
* Experience in academic and international industry 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 40%:
* 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 30%:
* Personal interview if applicable. #J-18808-Ljbffr

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