Stress response modelling in IceLab: PhD position in computational science to uncover the mechanisms of immune memory

The Department of Physics is looking for a PhD student in computational science with a focus on immune memory. The position is for four years of full-time doctoral studies. The employment starts in August 2025 or according to an agreement. The application deadline is February 16.

The research school for stress response modelling in IceLab
Starting in the spring of 2025, Umeå University’s interdisciplinary research hub, IceLab, will offer doctoral positions through the new Stress Response Modelling Research School.  Funded by the Knut and Alice Wallenberg Foundation and the Swedish Research Council’s centres of excellence, this research school focuses on modelling adaptive mechanisms in living systems under stress. It offers an extensive complexity science course package for doctoral students.

This doctoral position presents a unique opportunity to join a cohort of other doctoral researchers in the research school and learn alongside each other in carefully designed courses that align with the excellence centre’s multidisciplinary theme. 

The program prepares next-generation computational biologists with strong complexity thinking and tools applicable to living systems across organizational scales, addressing major environmental and life sciences challenges. 

Courses will cover topics such as complexity science, mathematical modelling in evolution, ecology and plant biology, along with transferable skills, including interdisciplinary communication and collaboration. You will also be offered opportunities for research exchanges and form an integral part of the supportive and stimulating IceLab research environment. 

Join IceLab to work at the forefront of multidisciplinary science, integrating mathematical modelling and data science with diverse disciplines, including ecology, plant physiology, and molecular biology. Your research will deepen our understanding of how living systems respond to stress and environmental change, and we will help you grow and thrive in your scientific career.

Read more about IceLab and the host department for this PhD position, the Department of Physics. 

Project description
This project integrates data science, machine learning, and mathematical modeling to investigate how the immune system adapts — or fails to adapt — under stress. The research focuses on individuals undergoing therapies that suppress immune cells, leaving them vulnerable to infections and reducing vaccine effectiveness. A key research question drives this work: What mechanisms govern immune cell dynamics and antibody production during stress responses in the immune system? 

To tackle this question, we will leverage unique technology that combines advanced sequencing with mass spectrometry, mapping immune responses in unprecedented detail. By analyzing this rich immune cell data, the project aims to uncover patterns in immune cell dynamics and identify what constitutes a successful antibody response. These findings will provide crucial insights for designing better vaccines and therapies in the future.

You will work with medical and computational experts to develop and apply tools for analyzing high-dimensional datasets, revealing the key drivers of immune function. The project includes collaboration with method developers at the Houston Methodist Research Institute in Texas, providing opportunities for research visits to engage with cutting-edge technology and expertise. This interdisciplinary research, supported by an exciting partnership, offers a unique opportunity to address pressing questions with real-world applications in public health.

Terms of employment
The position is intended to result in a doctoral degree. The main task of the PhD student is to pursue their doctoral studies, including participation in research and doctoral courses. The duties can include teaching and other departmental work (up to a maximum of 20%). The employment is limited to the equivalent of four years of full-time (48 months) or up to five years for teaching part-time. Salary is set in accordance with the established salary levels for PhD positions at Umeå University.

Competence requirements
To be admitted for studies at the third-cycle level, the applicant is required to have completed a second-cycle level degree or completed course requirements of at least 240 credits, of which at least 60 credits are at the second-cycle level or have an equivalent education from abroad or equivalent qualifications. 

To fulfil the specific entry requirements to be admitted for studies at the third-cycle level in CSE, the applicant is required to have completed courses at least 90 ECTS credits in CSE courses, of which at least 30 credits shall have been acquired at the second-cycle level. CSE courses refer to applied mathematics, computer science, physics or relevant fields. The requirements do not need to be fulfilled at the time of application but only at the enrollment.

The successful candidate should hold a master’s degree in physics, engineering physics, computer science, machine learning, bioinformatics, or a related field and have excellent skills in computational modeling. The candidate must have experience in machine learning or statistical modeling and proficiency in programming using modern languages. Familiarity with analyzing mass spectrometry or medical data is an advantage. The candidate should have a strong interest in interdisciplinary research and must be highly motivated and capable of working both independently and collaboratively within a research group. The candidate must be fluent in both oral and written English.

Application
The application should include the following:
1. A personal letter with a brief description of qualifications, research interests, and why you are interested in the position (max. 1 page)
2. Curriculum vitae.
3. Certified copies of relevant degree diploma(s).
4. A list of university courses with grades. Note that for international applicants the grading system should be explained in brief.
5. Copies of relevant work such as master’s thesis or articles you have authored or co-authored. If the master’s thesis has not been completed before the application deadline, a summary of the master’s thesis project and current progress shall be included. The summary can, at most, be five pages, including figures and references.
6. Contact information of three reference persons.

Applications must be submitted via e-recruitment system Varbi no later than 2025-02-16. All documents should be uploaded in pdf format.  

Information
For more information contact Martin Rosvall, martin.rosvall@umu.se, Johan Normark, johan.normark@umu.se or Mattias Forsell, mattias.forsell@umu.se. 

We look forward to receiving your application!