Postdoctoral researcher in Natural Language Processing und Research Knowledge Graphs (KTS-83)

SVERIGES LANTBRUKSUNIVERSITET

Department of Ecology The Swedish University of Agricultural Sciences (SLU) is one of Northern Europe largest academic hubs for ecological research and offers a dynamic and excellent research environment with modern infrastructure. The Department of Ecology has about 150 employees, of whom around 40 work at the Grimsö Research Station in Bergslagen. Together, the SLU Ecology Centre and Grimsö Research Station conduct research on sustainable agriculture and forestry, plant protection, nature conservation, and wildlife management, and provide scientific knowledge to inform Sweden and Europe’s environmental policies.   About the position Project Can we foresee the outcomes of public policies, political choices and other decisions? We are finding out by developing serious games and running them using AI. We are building large-scale simulations of societal processes (environmental negotiations, nature conservation policies, and hybrid-threat scenarios) in which every actor is an autonomous AI agent powered by Large Language Models (LLMs). These agents simulate real-world stakeholders, from government ministers to interest groups, and interact through natural language in complex strategic settings. We then run thousands of iterations to map the distribution of outcomes. This effort is part of a new research program Articulating Complexity ( https://www.slu.se/articulating-complexity/). We are looking for an ambitious post-doc to join this effort. Tasks and duties You are the person who makes the simulations meaningful. The technical infrastructure produces outputs in the form of thousands of LLM-generated texts from prompts. Your job is to ensure that these outputs are grounded in real human behavior, real political dynamics, and real institutional logic. Concretely this means: Scenario architecture. Each simulation is defined by a scenario with an initial world state, a cast of agents, communication channels, institutional constraints, document corpora. You will design scenarios focusing on negotiations of nature conservation policies and socio-ecological hybrid warfare. Agent persona construction. For each agent you will define the identity prompt, ideology vector, personality traits, decision mode weights, and the affect parameters that govern when agents escalate beyond their default moderation. This means extracting positions, rhetorical styles, strategic preferences, and psychological profiles from real-world sources. Analysis and validation of simulation outputs. After Monte Carlo runs, you will analyze the distribution of outcomes (e.g. which policies emerge) and will also design behavioural signature validation (e.g. verifying that simulated agents exhibit the expected action distributions when compared against empirical baselines). Publication and dissemination. You will co-author scientific publications from the project. The research will produce papers at the intersection of computational social science, ecology, security studies, and AI, a space with very few competitors and high visibility.  You will work closely with the PI (Guillaume Chapron https://www.slu.se/en/profilepages/c/guillaume-chapron/%20) and a research engineer in AI (recruited concurrently). The three of you will form the core team. Your profile Required A PhD in computational social science (or political science, psychology, behavioural economics, evolutionary anthropology or a related field) with strong quantitative skills. The PhD must be completed by the start date. Ability to reflect about strategic behaviour, political dynamics, or social processes in a structured, analytical way, whether through formal models, experiments or quantitative analysis. Willingness to work with AI and LLMs. You should be comfortable working critically with AI-generated outputs, interpreting how LLMs respond to instructions, and contributing to the design, testing, and refinement of prompts. Strong writing skills: clarity, precision, and the ability to communicate across disciplinary boundaries. Desirable Experience with agent-based modelling, game theory, simulation, or experimental methods in the social sciences. Experience with LLMs and their capabilities for simulating human behaviour such as the emerging literature on "silicon samples" and next-generation social simulations. Understanding of institutional design, legislative procedures, or multi-level governance. The simulation enforces procedural constraints, and designing these correctly requires knowing how real institutions actually work. Reading proficiency in Swedish, not required but an advantage. Assessment criteria Applications will be assessed on the following: Intellectual depth and originality. We are looking for someone who has demonstrated the ability to produce genuinely novel ideas, not incremental extensions of existing work. Your PhD thesis, publications, or research statement should show that you think independently and are drawn to hard, underexplored scientific problems. Interdisciplinary range. The ideal candidate is not easily captured by a single disciplinary label. If your work connects political behaviour, psychology, strategic interaction, and computational methods, even in an unconventional way, you are more interesting to us than a narrow specialist with a longer publication list. Fit with the project’s ambition. This is a project that aims to pioneer a new field and we want someone who finds that proposition thrilling rather than risky. Your application should make clear why this project, not just why a postdoc. Because the research area is new, you also need to be able to work in relative isolation. Cross-discipline disposition. You will work daily with questions from very different disciplines: computer science, AI, ecology, political science, geopolitics. The ability to communicate across disciplinary silos is essential. Interpersonal skills will form an important part of the assessment. Location: The position is based either at Grimsö or at Uppsala, with a possibility to be partly based at another Swedish academic institution with a core expertise in computational social science. Form of employment: Fixed-term employment 24 months, with possibility of extension. Scope: 100%. Start date: As agreed, as soon as possible after recruitment. Application: Please submit your application before deadline 14 July 2026. You can submit your application by clicking the button below. Application requirements are available on the SLU website.

SVERIGES LANTBRUKSUNIVERSITET

Department of Ecology The Swedish University of Agricultural Sciences (SLU) is one of Northern Europe largest academic hubs for ecological research and offers a dynamic and excellent research environment with modern infrastructure. The Department of Ecology has about 150 employees, of whom around 40 work at the Grimsö Research Station in Bergslagen. Together, the SLU Ecology Centre and Grimsö Research Station conduct research on sustainable agriculture and forestry, plant protection, nature conservation, and wildlife management, and provide scientific knowledge to inform Sweden and Europe’s environmental policies.   About the position Project Can we foresee the outcomes of public policies, political choices and other decisions? We are finding out by developing serious games and running them using AI. We are building large-scale simulations of societal processes (environmental negotiations, nature conservation policies, and hybrid-threat scenarios) in which every actor is an autonomous AI agent powered by Large Language Models (LLMs). These agents simulate real-world stakeholders, from government ministers to interest groups, and interact through natural language in complex strategic settings. We then run thousands of iterations to map the distribution of outcomes. This effort is part of a new research program Articulating Complexity ( https://www.slu.se/articulating-complexity/ ) hosted at the Swedish University of Agricultural Sciences (SLU) and led by Guillaume Chapron (Docent). It is funded by grants from the Swedish Research Council (VR), the Swedish Foundation for Strategic Environmental Research (Mistra), and the Swedish Research Council for Sustainable Development (FORMAS). Our goal is to build a novel methodology at the intersection of AI, ecology, political science, and complex system analysis that may change how policies are designed and stress-tested and how governments prepare for crises. We are looking for ambitious research engineer to join this effort. Tasks and duties You will be the person who makes the simulations actually run. Concretely, this means: Building the LLM-agent infrastructure (from an existing working implementation). Each agent has a multi-tier memory and an affect state that modifies both prompts and available actions, and a strategic reasoning layer that tracks reputation, commitments, and mental models of other agents. Extending and maintaining the multi-agent simulation framework. A simulation runs dozens of concurrent LLM instances, communicating through structured message-passing protocols. You will develop and maintain this framework, including the validation methodology. Running large-scale Monte Carlo simulations at scale on GPU-enabled HPC clusters (e.g. NAISS). Publishing and dissemination of the project results. You will co-author scientific publications from the project. The research will produce papers at the intersection of computational social science, ecology, security studies, and AI. You will work closely with the PI (Guillaume Chapron https://www.slu.se/en/profilepages/c/guillaume-chapron/) and a postdoctoral researcher in computational social science (to be recruited concurrently). The three of you will form the core team. Your profile Required A degree in computer science, engineering, physics, applied mathematics, or a related quantitative field. A Master or engineering degree is sufficient; a PhD is welcome but not required. Strong programming skills, especially in Python, and sufficient understanding of machine learning/deep learning to work effectively with modern generative AI systems. Ability to assess and incorporate cutting-edge generative AI developments into the project. Experience with software engineering practices such as version control, testing, documentation, modular design, and reproducible workflows. Ability to work independently, debug complex systems under time pressure, and take ownership of technical infrastructure. Desirable Experience with LLMs, including programmatic use through APIs and local deployment. The candidate should be able to select, configure, adapt, and critically evaluate LLMs for research applications. Experience with deep reinforcement learning, agent-based modelling, or multi-agent systems, including the design of simulation environments, interacting agents, decision rules, feedback mechanisms, and scenario-based analyses. Experience with high-performance computing: batch job submission, GPU workflows, and managing large-scale computational experiments. Interest in the application domain: nature conservation, environmental policy, political science, geopolitics and security studies, complex adaptive systems. You do not need a formal background in these fields, but you should find them interesting. Assessment criteria Applications will be assessed on the following: Demonstrated technical ability. We care more about what you have built, than about what courses you have taken. A GitHub portfolio, a deployed system, a well-documented side project, or a track record of solving hard AI problems will carry more weight than a list of credentials. Autonomy and resourcefulness. This is a small team doing frontier work, so the role requires someone who can diagnose problems independently, make pragmatic technical decisions, and keep complex systems running. If that excites rather than worries you, this is the right position. Collaborative disposition. You will work daily with questions from very different disciplines: ecology, political science, geopolitics. The ability to communicate technical constraints and possibilities to non-technical collaborators is essential. Interpersonal skills will form an important part of the assessment. Location: The position is based either at Grimsö or at Uppsala, with a possibility to be partly based at another academic Swedish institution with a core expertise in AI and machine learning. Form of employment:  Fixed-term employment 12 months with the possibility of prolongation.  Scope: 100%. Start date: As agreed, as soon as possible after recruitment.  Application: Please submit your application before deadline 14 July 2026. You can submit your application by clicking the button below. This is a shortened advertisement. Please refer to the full advertisement on the SLU website for complete information about the position and details on what to include with your application.

Constructor Knowledge Labs

ABOUT THE POSITION You are expected to conduct and lead internationally competitive research in AI-driven semantic analysis and automated reasoning-flow modeling, with applications to educational materials, scientific documents, and research authoring. Your work will focus on developing advanced methods for semantic structure extraction, conceptual and argumentative flow reconstruction, rationale-aware content generation, metacognitive prompting, and adaptive personalization. Core research contributions will include designing algorithms for concept and structure extraction, building neural/graph hybrid models for pedagogical reasoning, implementing ontology-alignment methods for cross-domain transfer, and creating human-in-the-loop optimization pipelines that incorporate expert feedback—aligning with the multi-year research roadmap (WP1–WP3) . As a postdoctoral researcher, you will take a leading role in designing experiments, shaping research directions, supervising junior researchers (including PhD students), and contributing to the development of end-to-end demonstrator systems capable of generating structured, rationale-rich, and learner-adaptive content. You will be responsible for coordinating data annotation efforts, overseeing the construction of evaluation frameworks, and driving publication-quality research outputs, including survey papers, methodology papers, and cross-domain transfer studies. Interdisciplinary collaboration is strongly encouraged, especially at the intersection of computer science, computational linguistics, cognitive science, and learning technologies, and you will have opportunities to initiate or co-lead joint projects with internal and external partners. The postdoctoral researcher will also contribute to teaching in areas such as Machine Learning, NLP, AI for Education, Explainable AI, and Python-based applied seminars, supporting course development and supervising Bachelor’s, Master’s, and PhD theses. The university provides a supportive academic environment—including mentoring, administrative support, computational resources, and opportunities for technology transfer and industry engagement—enabling the postdoctoral researcher to establish or strengthen an internationally visible research profile. ---------------------------------------------------------------------------------------------------------------------------------- MANDATORY REQUIREMENTS * PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a closely related field. * Strong publication record in relevant top-tier venues (e.g., NeurIPS, ACL, ICML, ICLR, AIED, LAK, AAAI). * Demonstrated expertise in at least two of the following areas: * semantic parsing or structured NLP * knowledge representation, reasoning graphs, or GNNs * natural language generation, explainability, or rationale modeling * ontology alignment, cross-domain transfer, or representation learning * personalization algorithms, metacognition, or educational AI * human-in-the-loop systems or RLHF * Experience in leading research tasks, mentoring junior researchers, and coordinating multi-stage projects. * Fluency in Python and modern deep learning frameworks (PyTorch/TensorFlow). * Strong analytical, communication, and academic writing skills. * Demonstrable ability to design rigorous experimental pipelines and validation methodologies. * Responsible, independent, and proactive research personality with strong teamwork skills. * Intercultural experience and readiness to work in an international research environment. * Fluency with AI co-pilot assistants for coding and writing. * Fluency in English, the primary language of research and instruction on campus. PREFERRED QUALIFICATIONS: * Experience in developing research prototypes, evaluation benchmarks, or large-scale datasets. * Prior involvement in interdisciplinary or applied research projects. * Potential to contribute to competitive funding applications. * Experience with open-source releases or reproducible research pipelines. APPLICATION DETAILS * Starting date: March, 2026 * Contract: Full-time (100%), TV-L E13 * Work mode: Hybrid APPLICATION PACKAGE MUST INCLUDE:  * Curriculum Vitae (CV); * A detailed letter of motivation outlining research interests and career goals; * 2 recommendation letters; Applications to be reviewed on a rolling basis. Shortlisted candidates will be invited to interviews.