Biomedical Engineering Sciences is characterised by its interdisciplinary profile, where research and education take place in the scientific field between medicine and technology.

The postgraduate education in Biomedical Engineering Sciences is individually tailored and based on the projects that you will be active in as a PhD student. This may include applied methods for the collection, processing, visualisation, and interpretation of medical and physiological data. In addition to applied research, you will be able to do research to describe and understand biological systems with engineering methods and explore methods to influence them.

These are our major research areas:

  • Biomedical Image Science
  • Biomedical Optics
  • Clinical Informatics
  • Health Informatics
  • Neuroengineering
  • Systems Biology
  • Tissue Engineering

Common to all research specialisations is that they aim to develop technological solutions that improve the ability of health and medical services to diagnose and treat patients and promote health. Research and postgraduate education also have a strong focus on utilising the results.

The postgraduate education is conducted at the Department of Biomedical Engineering (IMT), which is Sweden's first department in this field. Since 1970, IMT has been a pioneer in the development of medical engineering education and research, in Sweden as well as internationally.

IMT is located adjacent to the Linköping University Hospital. This enables interdisciplinary cutting-edge research in close collaboration with medical researchers. A clear manifestation of this is that several PhD students conduct parts of their research at the Center for Medical Image Science and Visualization (CMIV), which is part of Linköping University. There is also a tradition of organising PhD students' research and education in close collaboration with senior researchers and supervisors within the framework of major research projects.

Study syllabuses

Dissertations

2025

Kajsa Tunedal (2025) Unraveling Patient-Specific Mechanisms of Hypertension Using Mathematical Modeling and MRI (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789181183771
Elisabeth Klint (2025) Multimodal Brain Tumor Tissue Identification: Integration of Optical Guidance and Quantitative MRI in Neuronavigated Biopsies (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789181180244
Nathanael Göransson (2025) Metabolite and Electrode Alterations in Deep Brain Stimulation: Insights into Disease and Treatment (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789181181234

2024

Iulian Emil Tampu (2024) Deep learning for medical image analysis in cancer diagnosis (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789180757805
Christian Simonsson (2024) Mathematical Modelling of MASLD ‐ Towards Digital Twins in Liver Disease (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789180757348
Nicolas Sundqvist (2024) Mathematical Modelling of Cerebral Metabolism: From Ion Channels to Metabolic Fluxes (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789180755023

2023

Luigi Belcastro (2023) Multi-frequency SFDI: depth-resolved scattering models of wound healing (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789180753562
David Abramian (2023) Modern multimodal methods in brain MRI (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789180751360
Teresa Nordin (2023) Computational Models in Deep Brain Stimulation: Patient‐Specific Simulations, Tractography, and Group Analysis (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789179295349
Deneb Boito (2023) Diffusion MRI with generalised gradient waveforms: methods, models, and neuroimaging applications (Doctoral thesis, comprehensive summary) https://dx.doi.org/10.3384/9789180754439

Contact

Current PhD students at IMT

Doctoral studies at Linköping University