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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
of next generation agentic AI systems. In this PhD programme, you will redefine how the world works, learns, and discovers, turning bold ideas into tools used by millions. You will then become one
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implementation of research projects financed from national and international sources (e.g. NCN, Horizon Europe, ESA). Specific Requirements Research experience in computer science, artificial intelligence, machine
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Per Week 36.0 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 Do
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curriculum vitae (CV), transcripts and 300-word statement explaining your motivation for applying to this PhD Studentship to: Supervisor Review Form . Our supervisors will perform a comprehensive review to
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300-word statement explaining your motivation for applying to this PhD Studentship to: Supervisor Review Form . Our supervisors will perform a comprehensive review to long-list candidates. Deadline: 8
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combination of experimental work, rig development, and computational modelling, and will equip the student with a unique skill set highly relevant to both academic research and industrial careers such as
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an interest (or prior experience) in computational intelligence, AI and/or agent-based modeling techniques. He or she will work closely with researchers in the Electrical Engineering department at TU Eindhoven
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One fully funded, full-time PhD position to work with Alessandro Suglia in the Embodied, Situated, and Grounded Intelligence (ESGI) group at the School of Informatics, University of Edinburgh
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17 Oct 2025 Job Information Organisation/Company Universitat Politècnica de València Research Field Computer science Engineering Technology Researcher Profile First Stage Researcher (R1) Positions
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, information science, criminology or media and communication studies and who have training in quantitative methods (e.g., regressions, non-parametric, parametric tests, Structural Equation Modelling) and/or qualitative