Master’s Thesis: Deconstructing Reasoning Traces in LLMs

AI; Göteborgs kommun; Hybrid; SEK 201,000 - 268,000; Full time

Benefits offered by this job

Hybrid working mode

Access to substantial compute

Job summary

AI Sweden, Sweden’s national center for AI, invites a Master’s thesis student to join in collaboration with Stef SM Lab at Chalmers. The role focuses on adversarial robustness and honesty in reasoning traces, with work arranged as a thesis project at Lindholmen Science Park, Gothenburg, in hybrid mode.

You will design experiments, run open-weight reasoning models, and contribute to frontier AI safety research with access to substantial compute. Start date January 2027, deadline 2026-12-27.

Qualifications

• Ongoing Master’s studies in Computer Science, Data Science, Engineering Physics, Complex Adaptive Systems, Machine Learning, or similar.
• Comfortable with Python and deep learning frameworks; open to surprising experimental results.
• Prior experience with language models and reinforcement learning is a plus, but genuine curiosity and interest in AI safety and security matter most.

Responsibilities

• Design controlled experiments to understand the reasoning phenomenon.
• Run experiments on open-weight reasoning models and measure outcomes.
• Collaborate with AI Sweden researchers and leverage substantial compute resources.

Skills

Python

Deep learning

AI safety interest

Experiment design

Education

Master’s student in Computer Science/Data Science/ML

Tools

PyTorch/TensorFlow

Job description

As Sweden's national center for applied AI, we're on a mission to accelerate the use of AI to benefit our society, our competitiveness, and everyone living in Sweden. We drive impactful initiatives in areas such as healthcare, energy, and public services while pushing the boundaries of AI research in fields such as natural language processing, machine learning and AI security. Join us in harnessing the untapped value of AI to drive innovation and create sustainable value for Sweden.

We are now looking for an ambitious Master’s thesis student to join us at AI Sweden, in close collaboration with the Stef SM Lab at Chalmers University of Technology.

Background

Modern AI systems write out long chains of reasoning, checking their own work, backtracking when something looks wrong. A lot of the recent progress in AI capabilities has come from this, and most agentic systems now depend on it. But we understand surprisingly little about what these reasoning traces actually are. Is the written reasoning the computation, or a story told about a computation that happened elsewhere? Does a model that reasons longer become more reliable, or merely more confident? What are the parameters of reasoning as an attack surface against models? Reasoning traces are becoming a security control: if we can read a system's reasoning, we can audit it. That only works if the trace is honest, robust, and not something an adversary can steer.

The project

A project may focus on one of the following topics or combine several of them. The exact research question and methods will be decided together with the student, depending on the student's background and interests, previous work, and practical feasibility:

• Adversarial robustness for reasoning traces. Small changes injected into a model's reasoning pathway can have long-lasting, devastating effects. Can the model recover, or does it absorb the error and build on it? Does thinking longer help or hurt?

• Honesty. When a model backtracks on its own logic or decisions, does anything actually change inside it, or is the correction after the fact? Do reasoning traces define the intent, or are they just subvertible representations of it?

• Reasoning or recall? Is reasoning a recall mechanism (eliciting solutions that the model somehow already knows), or does it contribute to unlocking a fundamentally new class of solutions that would not be attainable otherwise?

• Visibility. Do reasoning traces reveal the full cognitive process, or are there other mechanisms behind the scenes that models rely on?

What you would do

Projects can be theoretical, computational, or a combination of the two. The main goal is to use a simplified model or controlled experiment to understand the reasoning phenomenon: Students will design controlled experiments, run them on open-weight reasoning models, and measure carefully. You will have access to substantial compute, and you will be working on questions that are genuinely open, in a frontier area of AI research, so there is a real chance your results are the first anyone has. The thesis can be done alone or in pairs.

Who we’re looking for

We are seeking a curious, independent, and self-driven MSc student who wants to work at the absolute frontier of AI research.

• Ongoing Master’s studies in Computer Science, Data Science, Engineering Physics, Complex Adaptive Systems, Machine Learning, or similar.

• You should be comfortable with Python and deep learning frameworks, and comfortable with the idea that an experiment might tell you something you did not expect.

• Prior experience with language models and reinforcement learning is a plus, but what matters most is a genuine curiosity and interest in AI safety and security.

At AI Sweden, we are committed to building diverse and inclusive teams. Some positions may be subject to export control regulations, which means that specific requirements may apply.

Why should you do your thesis with AI Sweden?

Doing your thesis at AI Sweden means working alongside leading AI scientists, change leaders, journalists, linguists, policy professionals and entrepreneurs—all working with a higher purpose in mind than “just” tech. AI Sweden is Sweden’s National Center for AI, we drive research questions that have both a long shelf-life and are widely applicable to Swedish industry and the public sector. We aim for publications at the most competitive venues and celebrate a culture of research excellence.
As an organization, we’re uniquely positioned at the sweet spot of governmental influence and startup agility. Small enough to stay adaptive and have fun but backed by and in close contact with both the government, academia and private and public sector. We offer our team members a place to grow, an environment for personal development and achievements.

Practical details

This Master’s thesis will be carried out at AI Sweden at Lindholmen Science Park, Gothenburg, in close collaboration with the Stef SM Lab https://stefsmlab.github.io/ at Chalmers. We aim for a hybrid working mode, with some time spent on-site, but there is room for flexibility.

Application Deadline: 2026-12-27, (rolling selection – position may be filled earlier).
Start Date: January 2027

Contact
Mauricio Muñoz, Senior Research Engineer and Project Lead at AI Sweden

AI Sweden does not accept unsolicited support and kindly ask not to be contacted by any advertisement agents, recruitment agencies or manning companies.