PhD Fellow in Trustworthy Generative AI with Knowledge Verification
Develop neuro-symbolic AI frameworks to verify and validate generative AI outputs in high-stakes domains like education and sustainability.
Best for:Best for computer science or engineering graduates with a strong background in AI, formal logic, and programming, seeking to contribute to trustworthy AI systems in high-stakes applications.
Overview
This PhD position at Oslo Metropolitan University focuses on creating a neuro-symbolic AI framework to address the critical issue of 'hallucinations' in generative AI models. The project aims to transform GenAI into auditable, verifiable, and socially responsible systems, particularly for high-risk and data-scarce domains such as North Sámi language learning, autonomous driving, and sustainability information modeling. The successful candidate will design, implement, and validate reasoning algorithms, collaborating with Karlsruhe Institute of Technology (KIT). The position offers a 3-year or 4-year contract with 75%–100% research focus, depending on career development needs, and is based in Oslo with potential relocation to Lillestrøm.
What you'll do
- Design and implement a neuro-symbolic AI framework to verify and validate outputs from generative AI models, ensuring factual correctness and source attribution.
- Develop reasoning algorithms that integrate semantic interpreters with symbolic logic modules for factual verification.
- Create and validate a modular verification engine for an AI-enhanced web platform focused on North Sámi language learning, ensuring linguistic correctness and cultural appropriateness.
- Explore additional use cases (e.g., autonomous driving and sustainability information modeling) to test the generalizability of the proposed framework.
- Collaborate with Karlsruhe Institute of Technology (KIT) on academic research and project development.
- Conduct research and publish findings in top-tier academic venues, contributing to the broader field of trustworthy AI.
Requirements
Degree required: Master's degree in computer science, mathematics, engineering, or an equivalent related discipline with at least 120 ECTS credits. Applicants with fewer than 120 ECTS must provide documentation proving their degree qualifies for doctoral studies in their country of origin.
Degree offered: PhD
Language: Written and oral proficiency in English (equivalent to IELTS 6.5 or TOEFL 90)
Instruction: English
- Strong programming skills, particularly in Python
- Analytical and mathematical background with a focus on formal logic and its application to generative models
- Familiarity with knowledge representation (e.g., knowledge graphs or semantic technologies)
- Experience with formal reasoning or related fields
- Ability to work independently and collaboratively on research projects
- Admission to the PhD programme in Engineering Science at Oslo Metropolitan University is required
- Minimum average grade B on subjects included in the master's degree
- Minimum grade B on the master's thesis
- Minimum average grade C on subjects included in the bachelor's degree (or first three years of an integrated master's degree)
- No specific nationality or residency restrictions, but applicants must meet Norwegian language requirements for employment
Funding & terms
How to apply
Deadline: 2026-11-18
Applicants must submit their application through Oslo Metropolitan University’s electronic recruitment system. Required documents include an application letter describing motivation, CV, reference letters, bachelor’s and master’s degree certificates, master’s thesis, scientific works or relevant links, a list of publications, and preferably two references with contact information. All documents must be in English or a Scandinavian language and authorized translations must be provided if necessary.
- Application letter describing motivation
- CV
- Reference letters
- Bachelor’s and master’s degree certificates
- Master’s thesis
- Scientific works or links to relevant publications
- List of publications and presentations at international seminars/conferences (if applicable)
- Two references with contact information
Contact
Baifan Zhou· Associate Professor
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.