PhD student in in Machine Learning building on physical principles - Hiring in process/Finished, not possible to apply

Are you interested in working in the intersection between machine learning and physics, 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 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.

The Division of Systems and Control enjoys a wide network of strong international collaborators all around the world, for example at the University of Cambridge, University of Oxford, Imperial College, University of Sydney, University of Newcastle and Aalto University. We strive for all PhD students to get a solid international experience during their PhD.

Project description
There are two main strategies to derive and deduce models – either using theory-based first principles or data-driven approaches. This project aims to conduct basic research to create new tools for using these two modeling strategies in conjunction. Combining all prior knowledge, both in terms of available data and physical first principles, has the potential to result in better models than if we only had to rely on one of them. How physics should be combined with data-driven machine learning models depends on the problem and is an active and in many areas still underdeveloped research field. 

By making machine learning models more physics-informed, they will also become more interpretable. This interpretability can transform these machine learning models from being black-box models into full-fledged scientific tools enabling new knowledge discoveries. Therefore, one aim of this project is to create machine learning models that not only can be leveraged by first principles, but in the future also can be used to enable new knowledge discoveries in the physical domains in which they are employed. Finally, the project also aims to use theories from physics to better understand why machine learning models are working, how they can be improved and quantify their fundamental limitations. 

We have a strong connection with collaborators in physics and materials science at Uppsala University, with a growing interest in using machine learning methods to advance knowledge in their respective domains. These collaborations can enable relevant applications as part of the project.

The exact research topic is decided in a dialogue between the doctoral student and the supervisor. The position is funded by the Swedish Research Council.

Duties
A doctoral student will devote the time to graduate education mainly. The rest of the duties may involve teaching at the Department, including also some administration, to at most 20%.

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

• hold a Master’s (second-cycle) degree in engineering physics, theoretical physics, applied mathematics, electrical engineering, data science 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.

Information about the specific entry requirements can be found in the study syllabus for the subject. Machine learning - Uppsala University (uu.se)

We are looking for candidates with

• a strong interest in machine learning and physics,
• good communication skills with sufficient proficiency in oral and written English,
• excellent study results,
• high proficiency in programming (preferably in Python),
• personal characteristics, such as a high level of 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, deep learning, optimization, signal processing, control theory, thermodynamics, statistical mechanics. 

Application
The application must include: 
1) a statement (at most 2 pages) of the applicant’s motivation for applying for this position, including 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) references with contact information (names, emails and telephone number) and up to two letters of recommendation. 

Applicants who meet at least one of the entry requirements are strongly encouraged to apply. All applicants should state their earliest possible starting date.

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

About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date 13/1 2025 or as agreed. Placement: Uppsala

For further information about the position, please contact: Associate professor Niklas Wahlström, niklas.wahlstrom@it.uu.se.

Please submit your application by 18 October 2024, UFV-PA 2024/2950.

Are you considering moving to Sweden to work at Uppsala University? Find out more about what it´s like to work and live in Sweden.