PhD student in biomedical engineering, deep learning for medical images

Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally leading computational and data science capabilities in Sweden. The program is funded with a total of 3.3 billion SEK over 12 years from the Knut and Alice Wallenberg (KAW) Foundation.

In 2026 the DDLS Research School will be expanded with the recruitment of 25 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/

The future of life science is data-driven. Will you be part of that change? Then join us in this unique program!

At Linköping University, we are announcing the position as DDLS PhD student in Data-driven precision medicine and diagnostics

Data-driven precision medicine and diagnostics covers data integration, analysis, visualization, and data interpretation for patient stratification, discovery of biomarkers for disease risks, diagnosis, drug response and monitoring of health. The precision medicine research is expected to make use of existing strong assets in Sweden and abroad, such as molecular data (e.g. omics), imaging, electronic health care records, longitudinal patient and population registries and biobanks.

Your work assignments

The position focuses on developing methods for early detection of lung cancer, through fusion of chest CT volumes and clinical variables. Within the Swedish project SCAPIS, medical images and clinical variables have been collected for more than 30,000 subjects. The goal is to use this dataset to train models for early detection of lung cancer (lung nodules), and also determine if the lung nodules are benign or malignant. Since CT volumes are of very high resolution, it is necessary to develop new methods to efficiently detect all lung nodules. By combining CT volumes and clinical variables (such as age, sex, smoking status), the goal is to make the methods even better at separating benign and malignant nodules. You will become an expert in analyzing large medical datasets, and also gain knowledge on how AI can be used in healthcare.

The position involves many different types of meetings with other PhD students, researchers, supervisors, and collaborators. You are therefore expected to be able to engage in discussions and reason about matters related to your role.

As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20 per cent of full-time.

Your qualifications

You have graduated at Master’s level in biomedical engineering, electrical engineering, machine learning, statistics, computer science, or a related area considered relevant for the research topic, or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses. Alternatively, you have gained essentially corresponding knowledge in another way.

Specific eligibility for doctoral education in Biomedical Engineering Science is granted to those who have completed course requirements of at least 60 higher education credits at an advanced level in a field relevant to the doctoral subject. The applicant must also be able to demonstrate documented proficiency in English. 

You have knowledge and expertise in computer vision and/or medical image analysis, deep learning as well as mathematics. You have substantial expertise in programming, especially in Python.

You are independent, meticulous and work efficiently. This position requires good communication skills: You enjoy actively participating in meetings and have a strong ability to express yourself verbally, as well as to engage in discussions and reasoning together with others.

Your workplace

Linköping University is one of the leading AI institutions in Sweden. We have strong links to prominent national research initiatives, such as DDLS, WASP and ELLIIT. You will have access to state-of-the-art computing infrastructure for machine learning, e.g. through Berzelius as well as powerful local computers.

You will work at the Division of biomedical engineering IMT, which conducts research within many different projects connecting medicine and engineering. The available position is within a research group which develops methods for analysis of medical images. The group collaborates with several medical doctors at Linköping University hospital, through CMIV, with different types of expertise. The group also collaborates with other divisions at Linköping University; mainly the computer vision laboratory at the department of electrical engineering (focusing on deep learning for computer vision), and the division of statistics and machine learning at the department of computer and information science (focusing on the theory behind machine learning).

The employment

When taking up the post, you will be admitted to the program for doctoral studies in Biomedical Engineering Sciences. More information about the doctoral studies at each faculty is available at Doctoral studies at Linköping University

The employment has a duration of normally four years’ full-time equivalent. Extension of employment up to five years is based on the degree of teaching and institutional assignment. Further extensions may be granted in exceptional circumstances. You will initially be employed for one year, after which your employment will be renewed for a maximum of two years at a time, depending on your progress through the study plan. 

Start as soon as possible or by agreement. 

Salary and employment benefits

The salary of PhD students is determined according to a locally negotiated salary progression. 

More information about employment benefits at Linköping University is available here.

Union representatives

Information about union representatives, see Help for applicants.

Application procedure

Apply for the position by clicking the “Apply” button below. Your application must reach Linköping University no later than 2026-05-15 (CET).

Applications and documents received after the date above will not be considered.