PhD student in Machine learning with applications in precision medicine

Are you in interested developing new machine learning methods for precision medicine and clinical decision support, together with competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a PhD position at the Department of Information Technology, Uppsala University.

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, with 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 network science, spanning diverse application domains such as energy systems, biomedical systems, material science, and safety and security. We have 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 Tübingen, University of Sydney, and Aalto University. We strive for all PhD students to get a solid international experience during their PhD.

Project description
Machine learning methods hold the potential to advance precision medicine and clinical decision support. At the same time, these application areas present new challenges for statistical learning methodology. They involve high-stakes decisions with important trade-offs and uncertainties. They are also challenged by the data sampling process which gives rise to distribution shifts when comparing past and future data.

This project is focused on basic research into theory and methods that can address these novel challenges. The aim is to develop new ideas and methods that can tackle the uncertainties and make explicit the relevant clinical trade-offs in predictive and prescriptive machine learning methods. The research will also involve interactions with our clinical partners at Uppsala University Hospital (Akademiska sjukhuset). 

Duties
The doctoral student will primarily devote their time to graduate education. Other departmental duties of at most 20%, including teaching and administration, may also be included in the employment.

Requirements
Entry requirements for doctoral education are regulated in the Higher Education Ordinance. To meet the general entry requirements for doctoral studies, you must: 

• hold a Master’s (second-cycle) degree in in engineering physics, electrical engineering, applied mathematics, mathematical statistics, 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:

• a solid mathematical foundation and an interest in statistical learning,
• good communication skills with sufficient proficiency in oral and written English,
• excellent study results,
• high proficiency in programming (preferably in Python, Julia or Matlab),
• 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: estimation theory, statistical machine learning, optimization, signal processing, system identification, or control theory.

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 August 20, 2025, or as agreed. Placement: Uppsala.

For further information about the position, please contact: Dave Zachariah, e-mail: dave.zachariah@it.uu.se.

Please submit your application by April 7, 2025, UFV-PA 2025/364. 

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