Vacant job

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We are looking for a PhD candidate in statistics and machine learning.

Your tasks

We are seeking a PhD candidate who wants to work at the intersection of computational statistics and machine learning, with a particular focus on methods based on differential equations. The research will be fundamentally oriented, and the overall mission is to develop computationally efficient and statistically principled new models and methods for modern machine learning problems.

Methods based on differential equations have become central in modern machine learning, e.g., generative diffusion models. These models have a number of important application areas, such as image and material generation, scientific computation, and Bayesian inverse problems. Your main research tasks will be to develop new models and methods for generative sampling and Bayesian inference.

You will be jointly supervised by Zheng Zhao (https://zz.zabemon.com (https://zz.zabemon.com)) and Fredrik Lindsten (https://scholar.google.com/citations?user=GylfPngAAAAJ (https://scholar.google.com/citations?user=GylfPngAAAAJ)).

As a PhD candidate, you will dedicate yourself to your doctoral education and the research projects you are involved in. Your work may also include teaching or participating in other departmental tasks, up to 20 percent of full-time.

Your qualifications

You have completed a master's degree in applied mathematics, statistics, machine learning, control engineering, computer science, or a related field deemed relevant to the research problems of the project, or completed courses totaling at least 240 higher education credits, of which at least 60 higher education credits at the advanced level in one of the aforementioned areas or acquired equivalent knowledge in another way.

For the position, very good knowledge of English, both spoken and written, as well as the ability to collaborate and communicate effectively are required.

Experience in one or more of the following areas is considered particularly meritorious: stochastic (partial) differential equations, regulated differential equations, generative diffusion models, flow models, optimal transport, stochastic filtering, sequential Monte Carlo, Markov chain Monte Carlo, Bayesian inference, and inverse problems.

Excellent academic results, a solid background in mathematics and statistics, and strong motivation in theoretical and methodological research are particularly meritorious. Experience with statistical machine learning models and methods, Bayesian machine learning, or a related area mentioned in the “tasks” is also particularly meritorious.

Good programming skills in Python. Experience with JAX/Julia is meritorious.

Your workplace

The position is formally placed at the Department of Statistics and Machine Learning (STIMA) at the Department of Computer Science. At STIMA, we conduct research and education in both statistics and machine learning, at the undergraduate, advanced, and doctoral levels. We regularly publish substantial contributions at the best machine learning conferences (e.g., ICML, ICLR, NeurIPS). STIMA is characterized by a modern view of the statistical subject, where probabilistic models are combined with computational algorithms to solve challenging complex problems, as well as a statistical view of machine learning that clearly integrates the two subject areas within the department. For more information about STIMA, see https://liu.se/organisation/liu/ida/stima (https://liu.se/organisation/liu/ida/stima).

Linköping University is one of the leading AI institutions in Sweden. We have strong connections to prominent national research initiatives, such as WASP and ELLIIT. You will have access to state-of-the-art computing infrastructure for machine learning, e.g., through Berzelius. Linköping University will also host EuroHPC Arrhenius and a European AI Factory (MIMER), as one of the seven sites in Europe selected in the first round. Linköping recently won the European Capital of Innovation Awards as the European Rising Innovative city.

About the employment

Upon taking up the position, you will be admitted to the doctoral program. Read more about the doctoral education at each faculty here.

The employment is time-limited to normally four years full-time. Extension of employment up to five years occurs based on the degree of teaching and departmental tasks. In special cases, further extension may occur. You will initially be employed for one year, and thereafter the employment will be renewed for a maximum of two years at a time, based on the achieved study plan.

Start date by agreement.

Salary and benefits

The PhD salary is regulated according to a locally agreed salary scale. Read more about employee benefits here.

Union contacts

Information about union contacts can be found in Help for applicants.

Application

You apply for this position by clicking the “Apply” button below. Your application must be received by Linköping University no later than April 10, 2026.

Applications received after the deadline will not be considered.

In your application, please attach:

• A personal letter (max 1 page) briefly describing yourself. It is important that you explain why you are motivated to apply for this position and how you fit in.
• CV.
• Study documents from undergraduate and master's studies in English or Swedish.
• A copy of your master's thesis and degree certificate. If you have not yet graduated, please attach a document briefly describing your thesis work and current status.
• Contact information for referees (and reference letters if available).

Applicants with an international background and from underrepresented groups are more than welcome to apply.

We welcome applicants with diverse backgrounds, experiences, and perspectives, as this enriches and develops our activities. For us, it is self-evident to uphold everyone's equal value, rights, and opportunities. Read about our work with Equal Opportunities.

Welcome with your application!

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