Agentic AI Scientist | Informatics Engineering (or related area) | Intelligent Systems Team (Job Ref.: AICOS_Jobs_2025_27) | Porto, Portugal | English Version
Job Title: Agentic AI Scientist
Job Ref: AICOS_Jobs_2025_27
General scientific field: Engineering
Specific scientific field: Informatics Engineering (or related area)
Associação Fraunhofer Portugal Research opens an international call for PhD holders under a non‑fixed work contract with an expected duration of 12 months.
Announcement for one researcher position to conduct activities within the following projects (if approved):
AI4CarOps – AI‑Powered Vehicle Reception Operations for Car Workshops, with Notice No. MPr‑2023‑07 SIID I&D Empresarial and Project Reference No. 18234 – COMPETE 2030 Copromoção.
FibFlow – Financial Intelligent Business Flow, with Notice No. MPr‑2023‑08 SIID I&D Empresarial and Project Reference No. 20856 – COMPETE 2030 Copromoção.
Microelectrónica – Agenda Microeletrónica, with Notice No. 01/C05‑i01/2021 and Project Reference No. 19 – NextGenerationEU (PRR) Copromoção.
NextGenAI – Center for Responsible AI, with Notice No. 01/C05‑i01/2021 and Project Reference No. 62 – NextGenerationEU (PRR) Copromoção.
DigitalFOOD – Fostering AI adoption in the Portuguese Food Industry, Project Proposal submitted within Notice No. COMPETE2030‑2025‑4 – COMPETE 2030 SIAC Digitalização.
RAICC – Responsible AI Call Center, Project Proposal submitted within Notice No. MPr‑2025‑01 SIID I&D&I Empresarial – COMPETE 2030 Copromoção.
The research will focus on Large‑Language Models, Retrieval‑Augmented Generation (RAG) and Agentic AI, with the goal of developing reliable, policy‑compliant AI methodologies for critical domains, automating complex data‑intensive tasks, and establishing robust evaluation protocols for AI response quality.
The Work Plan Includes The Following Tasks:
Research, implement, and validate pioneering Retrieval‑Augmented Generation methodologies in real‑world settings, including creating policy‑sensitive RAGs that comply with regulatory documents and integrating semi‑automated compliance checks.
Automate repetitive business tasks by extracting and structuring data from documents and designing AI models to provide categorization recommendations based on extracted information.
Continuously assess complex documentation using advanced Large‑Language Models to provide context‑aware risk assessments, generating dynamic reports and risk scores.
Develop specific metrics and protocols to evaluate the quality of AI‑based systems.
Conduct AI training and the creation of proof‑of‑concepts (PoCs) for new applications.
Applicable Legislation and Work Conditions
Decree‑Law no. 57/2016, amended by Law 57/2017 and Regulatory Decree No. 11‑A/2017, Portuguese Labor Code, Law 7/2009, and related employment regulations.
Hiring panel composed of Inês Nunes de Sousa Soares (PhD; Head of Department), Luís Filipe Caeiro Margalho Guerra Rosado (PhD; Permanent Member), and André Valério Raposo Carreiro (PhD; Permanent Member).
Workplace at Associação Fraunhofer Portugal Research – Rua Alfredo Allen 455/461, 4200‑135 Porto, Portugal – travel may be involved.
Monthly remuneration: €2,622.59, level 38 of the remuneration table.
Application can be submitted by any national, foreign, and stateless candidate holding a doctorate degree in Informatics Engineering or related area, meeting the formalities required by Decree‑Law no. 66/2018.
Requirements – Experience and Skills
Experience in Generative AI, Large Language Models, reinforcement learning, recommender systems, and multi‑agent systems.
Research experience in Responsible AI.
Experience with designing and architecting end‑to‑end evaluation pipelines and benchmarking for AI‑based systems.
Relevant hands‑on experience in AI solutions design, development and implementation.
Teaching, supervision, and mentoring experience relevant to the scientific domain.
Successful experience in research proposal writing.
Programming proficiency in Python and experience with machine learning frameworks such as PyTorch and TensorFlow.
Proficiency in English and Portuguese.
Evaluation Criteria
Scientific coherence of CV – 15%.
Diversity and quality of scientific indicators – 5%.