Job for Researchers: Research Engineer in AI-driven Social Simulations — SLU, Sweden

About the role

The Department of Ecology at the Swedish University of Agricultural Sciences (SLU) is seeking an ambitious Research Engineer in AI-driven Social Simulations to join a new research program called Articulating Complexity. This project develops large-scale simulations of societal processes—such as environmental negotiations, nature conservation policies, and hybrid-threat scenarios—where every actor is an autonomous AI agent powered by Large Language Models (LLMs). By running thousands of Monte Carlo iterations, the team maps the distribution of outcomes to help foresee the effects of public policies, political choices, and other decisions. The position is funded by the Swedish Research Council (VR), the Swedish Foundation for Strategic Environmental Research (Mistra), and the Swedish Research Council for Sustainable Development (FORMAS).

Responsibilities

• Build and extend the LLM-agent infrastructure from an existing working implementation, including multi-tier memory, affect states, and strategic reasoning layers.
• Develop and maintain the multi-agent simulation framework that runs dozens of concurrent LLM instances with structured message-passing protocols, plus the validation methodology.
• Run large-scale Monte Carlo simulations on GPU-enabled HPC clusters (e.g., NAISS).
• Co-author scientific publications at the intersection of computational social science, ecology, security studies, and AI.
• Work closely with the PI (Guillaume Chapron) and a concurrently recruited postdoctoral researcher in computational social science as part of a small core team.

Requirements

Required

• Strong programming skills in Python and sufficient understanding of machine learning/deep learning to work with modern generative AI systems.
• Ability to assess and incorporate cutting-edge generative AI developments.
• Experience with software engineering practices: 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, and the ability to select, configure, adapt, and critically evaluate them for research.
• Experience with deep reinforcement learning, agent-based modelling, or multi-agent systems—including simulation environments, interacting agents, decision rules, and scenario-based analyses.
• Experience with high-performance computing: batch job submission, GPU workflows, and managing large-scale computational experiments.
• Interest in application domains such as nature conservation, environmental policy, political science, geopolitics, security studies, and complex adaptive systems (formal background not required).

Assessment criteria

• Demonstrated technical ability: A GitHub portfolio, deployed system, well-documented side project, or track record of solving hard AI problems will carry more weight than a list of credentials.
• Autonomy and resourcefulness: The role requires diagnosing problems independently, making pragmatic technical decisions, and keeping complex systems running.
• Collaborative disposition: Ability to communicate technical constraints and possibilities to non-technical collaborators from ecology, political science, and geopolitics is essential.

What we offer

SLU is one of Northern Europe’s largest academic hubs for ecological research, offering a dynamic and excellent research environment with modern infrastructure. The Department of Ecology has about 150 employees, around 40 of whom work at the Grimsö Research Station in Bergslagen. Together with the SLU Ecology Centre, the department conducts research on sustainable agriculture and forestry, plant protection, nature conservation, and wildlife management, and provides scientific knowledge to inform Sweden’s and Europe’s environmental policies. You will join a program that aims to build a novel methodology at the intersection of AI, ecology, political science, and complex system analysis.

Location

The position is based either at Grimsö or at Uppsala, with a possibility to be partly based at another Swedish academic institution with core expertise in AI and machine learning.

How to apply

Applications will be assessed on the criteria above. For inquiries, contact [email protected].

Original vacancy