Arbetsbeskrivning

Do you want to develop the next generation of LLM agents that support deep learning research, model development, and code generation? Join us at the Division of Computing Science, Department of Computer Science and Engineering, and contribute to research on autonomous AI systems for accelerating research and innovation. 

About us 

The Department of Computer Science and Engineering, a joint department of Chalmers and the University of Gothenburg, spans the breadth of computing disciplines. Our internationally visible research, strong industry links and diverse environment create a collaborative setting where ideas grow into real impact. 

At the division of Computer Science, we advance secure and trustworthy software and systems, spanning foundations, programming languages, tools and practical methods that help shape dependable digital infrastructures. 

The position will be part of AIXLab (www.usableai.se), a research environment focused on making AI systems more usable, reliable, and useful in real-world settings. AIX Lab develops methods and tools for deep learning, foundation models, LLM agents, automated machine learning, and AI-enabled software engineering, with a strong emphasis on practical evaluation and collaboration with industry. The lab works across application areas such as software development, automotive, healthcare, accessibility, sustainability, and industrial AI, aiming to bridge technical AI research with real-world needs and impact.

About the research project  

This project investigates LLM agents for autoresearch, with a focus on supporting both deep learning research and software development workflows. The goal is to develop agentic AI systems that can assist researchers and developers in formulating hypotheses, designing experiments, implementing models, generating and revising code, debugging software, analyzing results, managing research knowledge, and improving the reproducibility of both machine learning and software engineering processes.

The project will study how LLM agents can support the full lifecycle of technical research and development, from idea generation and literature exploration to model implementation, software prototyping, testing, evaluation, and documentation. The developed methods and prototypes will be continuously evaluated together with industrial partners to ensure practical relevance, robustness, and usefulness in real-world development environments.

Who we are looking for 

The following requirements are mandatory: 

• A doctoral degree in computer science, artificial intelligence, machine learning, or a closely related field. This eligibility requirement must be met no later than the time the employment decision is made.
• Strong research experience in at least one of the following areas: deep learning, machine learning, AI-assisted software development, or automated machine learning.
• Strong programming skills, preferably in Python and modern software development environments.
• Experience with deep learning frameworks, such as PyTorch, TensorFlow, JAX, or equivalent, or strong experience with research-oriented software development.
• Strong written and verbal communication skills in English.
• Ability to work independently and drive research tasks from idea to implementation and publication.
• Ability to collaborate in a research group and contribute constructively to joint projects, supervision, and scientific discussions.

You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education. 

The following experience will strengthen your application: 

• Research experience with large language models, foundation models, LLM agents, tool-using LLMs, retrieval-augmented generation, or multi-agent systems.
• Experience with code generation, program synthesis, automated debugging, software testing, program repair, or AI-assisted software development.
• Experience with deep learning model development, including model design, training, evaluation, ablation studies, and benchmarking.
• Experience with automated machine learning, neural architecture search, meta-learning, data-centric AI, or automated experimentation.
• Publications in relevant venues in machine learning, artificial intelligence, or software engineering.

What you will do 

• Develop LLM-agent methods and prototypes for deep learning workflows, software development, code generation, debugging, testing, and documentation.
• Evaluate the developed methods in controlled experimental environments using benchmarks, reproducible test cases, and systematic comparisons.
• Evaluate the methods continuously together with industrial partners in realistic development environments.
• Publish high-quality scientific papers in relevant venues in AI, machine learning, software engineering, and applied AI.
• Engage in teaching at undergraduate/master’s level including thesis supervision.

The position is meritorious for future roles in academia, industry, or the public sector. 

Contract terms  

The position is a temporary full-time employment for two years with the possibility of a one-year extension. 

The position requires physical presence at Chalmers throughout the entire employment. A valid residence permit must be presented by the start date, otherwise the offer may be withdrawn. 

What we offer 

Read more about what we offer at the Chalmers' vacancy page.

Application procedure 

Read more about how to apply on the Chalmers vacancy page. 

A background check may be conducted as part of the application process.

Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered. Contact details to references will be requested after the interview. 

We welcome your application no later than July 3rd, 2026.  

For questions please contact: 

Yinan Yu 

Assistant [email protected]

We look forward to your application! 

Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position.