PhD student in Machine Learning - Models evolving over space and time - Hiring in process/Finished, not possible to apply

Are you interested in working with machine learning methods with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favorable working conditions? We welcome you to apply for a PhD position at Uppsala University. 

Uppsala University has a long tradition of successful research – among its alumni are 16 Nobel Prize laureates, including, most recently, Svante Pääbo. The University is unique when it comes to combining IT with wider research, from life sciences to the humanities, and this collaboration is currently facilitated by AI4Research and the Centre for Interdisciplinary Mathematics.

The Department of Information Technology holds a leading position in both research and education at all levels. We are currently Uppsala University's third largest department, have around 350 employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the Department of Information Technology website.

At the Division of Systems and Control, we develop and analyze both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical systems, neuroscience, and safety and security. We have a wide network of long-standing international collaborators all around the world, for example at the University of Cambridge, University of Oxford, University of Sydney, University of Newcastle and Aalto University. We offer all our PhD students the opportunity to get international experience during their PhD.

We offer a PhD student position to explore and develop Machine Learning models evolving  over space and time and to make use of these models to understand the organization of DNA and its relation to the dynamic 3D-structured chromosomes. The student will form a part of our new NEST initiative funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP) and the Wallenberg National Program for Data-Driven Life Science (DDLS). Our project, Learning 3D Genome Dynamics from Heterogeneous Data, is a 5-year collaboration between researchers at Uppsala University and Karolinska Institute. The overall objective is to develop and make use of machine learning methods to help us understand the organization of life.

Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems.  The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry. Read more: https://wasp-sweden.org/ 

Project description
This project focuses on developing, analyzing and using probabilistic methods for dynamic  phenomena evolving over space and time based on measurements from different and complementary sources. We will develop generally applicable machine learning models and methods driven by the data-rich experiments from our collaborators. The real-world use-case is to learn the rules that govern the dynamics of the bacterial chromosome structure.

Technical building blocks could include state-space models, generative models in the form of diffusion models, deep learning, optimal transport, and probabilistic modelling in general. Computer vision can also be included if there is interest.

The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry. Read more: https://wasp-sweden.org/graduate-school/

Duties
The position is for a maximum of five years and can include departmental duties at a level of at most 20% (typically teaching).

The doctoral position involves the development of theory and probabilistic methods for phenomena evolving over time and space. Related to this is the task of deriving algorithms that can be used to learn the unknown model parameters from the measured data. The position involves collaboration within the NEST project partner groups of Johan Elf and Magda Bienko.

Requirements
To meet the entry requirements for doctoral studies, you must: 

• hold a Master’s (second-cycle) degree in engineering physics, computer science, electrical engineering, applied mathematics, machine learning, or in a similar field, or
• have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including an independent project worth at least 15 credits, or 
• have acquired substantially equivalent knowledge in some other way.

The University may permit an exemption from the general entry requirements for an individual applicant, if there are special grounds (Chapter 7, § 39 of the Higher Education Ordinance). For special entry requirements, please see the subject’s general study plan.

We are looking for candidates with:

• an interest in developing Machine Learning methods and models,
• ability to communicate technical material effectively in oral and written form (English),
• very good study results,
• good working knowledge in programming (preferably in Python),
• personal characteristics, such as a creativity, thoroughness, and/or a structured approach to problem-solving are essential.

Additional qualifications
Experience and courses in one or more subjects are valued: machine learning, optimisation, linear algebra, deep learning, programming, dynamical systems.

Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines.

Application
The application must include:

1. A cover letter (max 2 pages), in English, briefly describing your motivation for applying for this position and the earliest possible employment date. The cover letter should include the heading Suitability for this position, containing a self-assessment on why you would be the right candidate for this position;
2. a CV;
3. degrees and transcript of records with grades (translated to English or Swedish);
4. the Master’s thesis (or a draft thereof, and/or some other self-produced technical or scientific text), publications, and other relevant documents;
5. Two references with contact information (names, emails and telephone number) and up to two letters of recommendation. 

About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date on February 1, 2026 or as otherwise agreed. Placement: Uppsala.

For further information about the position, please contact: Professor Thomas Schön (e-mail: thomas.schon@it.uu.se), Assistant Professor Isabel Hassler (e-mail:  isabel.haasler@it.uu.se) or Professor Johan Elf (e-mail: johan.elf@icm.uu.se).

Please submit your application by November 27, 2025, UFV-PA 2025/3121.

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