Postdoc in Trustworthy Generative AI Research – Gothenburg, Sweden | Visa + Salary Insights

📍 Location: eu

🏷 Type: Full-time

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Job Overview

This Postdoctoral Researcher in Trustworthy Generative AI position at Chalmers University of Technology in Gothenburg focuses on advancing neural-symbolic AI systems to improve reliability, safety, and verifiability of large-scale generative models such as LLMs and VLMs. The role is part of the EU Horizon Europe project RobustifAI, targeting real-world applications in robotics and healthcare. The ideal candidate is a highly skilled AI researcher with strong publication history, deep ML expertise, and interest in AI safety, verification, and autonomous systems. This is a senior-level postdoctoral research role requiring independent leadership and collaboration across European research partners.

📅 Job Timeline & Status

This role is in an active recruitment phase with a clearly defined deadline. Given its EU-funded research nature and limited postdoc slots, competition is expected to intensify closer to the deadline. Applicants should treat this as a high-priority application window and apply early to maximize visibility before the review committee shortlists candidates.

🌍 Work Eligibility & Location

This is a fully Onsite research position in Gothenburg, Sweden. Candidates must be physically present throughout employment, and valid residence authorization is required before start. While Swedish language skills are not mandatory, integration support including language courses is provided, making this role accessible to international researchers.

💰 Salary Intelligence

Compensation aligns with Swedish academic postdoctoral standards, which are generally competitive in Europe with strong benefits including healthcare, parental leave, and pension contributions. While base salary is not disclosed, total compensation is enhanced by Sweden’s strong social benefit system and research funding stability.

📊 Role Breakdown

This role focuses heavily on trustworthy generative AI, combining machine learning (ML), formal verification, and neural-symbolic reasoning. Approximately 40% of the work involves designing novel AI architectures, 30% involves empirical evaluation and benchmarking in robotics contexts, 20% involves collaboration across EU partners, and 10% covers supervision and academic contributions. You will actively work on improving the safety and reliability of LLMs, VLMs, and autonomous robotic systems. A significant focus is placed on developing methods that allow AI systems to generate outputs that are not only accurate but also verifiable and aligned with real-world constraints.

You will contribute to the RobustifAI project by designing verification frameworks for generative models, implementing neural-symbolic pipelines, and testing systems in robotics environments such as elderly-care assistants. Expect hands-on work with Python-based ML stacks, deep learning frameworks, and robotics simulation environments. Collaboration with European research labs is central, requiring strong communication and publication-driven execution.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a highly selective research role requiring proven academic impact in AI or machine learning. Candidates are expected to demonstrate publication strength in leading venues and the ability to independently lead research directions. The intersection of AI safety, generative models, and robotics significantly increases competitiveness.

🚀 Career Impact

This role significantly strengthens long-term positioning in AI research leadership, particularly in trustworthy AI and robotics integration. Experience gained here is directly transferable to elite academic institutions and advanced industry research labs focused on AI alignment and safety systems.

📋 Key Responsibilities

You will lead research initiatives in trustworthy generative AI systems, focusing on designing and validating neural-symbolic architectures. Core responsibilities include developing methods for AI verification, robustness testing, and safe generation constraints. You will prototype and evaluate models such as LLMs and VLMs in controlled robotics environments, particularly service robots for healthcare use cases.

Additional responsibilities include supervising master’s and PhD students, contributing to EU-wide research collaborations, and publishing in top-tier AI conferences. You will also be expected to design experiments, implement scalable ML pipelines in Python and deep learning frameworks, and contribute to the scientific direction of the RobustifAI project. Teaching involvement may also be included at undergraduate or graduate level.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

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🧠 Fit & Positioning Analysis

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📅 Application Signals

This role shows strong mid-to-late recruitment momentum with a fixed deadline of 2026-06-28. Given EU research funding cycles, applicant volume is expected to increase sharply in the final two weeks. The competition level is high, particularly from PhD graduates in AI safety and robotics.

Candidates should expect a structured review process with interviews scheduled shortly after the deadline. Strong applicants may receive early contact, but most decisions will occur post-deadline. Due to international visibility of Chalmers and the AI safety focus, this role is likely to attract global applications.

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✅ Job Source & Verification

This listing is based on an official posting from Chalmers University of Technology, a highly credible European research institution. Information is consistent with EU Horizon Europe project documentation and verified as of 2026-05-31. The data reflects a recently published and actively maintained academic job call with high reliability.