PhD student to the Research Group in Radiological Image Analysis

The section of Radiology at the Department of Surgical Sciences, Uppsala University, is organized in several research groups that conduct research within the development and application of imaging and functional diagnostic methods. These methods are used in everything from experimental research to clinical studies on patients and large-scale epidemiological studies on volunteers. In the Radiological Image Analysis research group, we specialize in advanced image analysis methods for research applications related to metabolic and cardiovascular disease as well as cancer. The group members have interdisciplinary backgrounds and expertise to foster cutting-edge research with high clinical relevance.

Project Description 
Imaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography combined with CT (PET/CT) are routinely used in healthcare to diagnose and monitor various conditions and treatments. However, manual visual inspection of, or measurements from, the extensive image information requires great accuracy and is therefore time-consuming. Today, detailed image information is collected from MRI and CT systems on a large scale in various cohort studies, often together with data from clinics, genomics, proteomics, and metabolomics. Our research group has developed several advanced methods for integrated analysis of the detailed image data and all other collected information. The techniques include image registration, segmentation, and regression/classification, often include deep learning-base implementations.

Together with experts in epidemiology, genetic, and multi-omics analyses, we have been granted funding from DDLS in the field of data-driven precision medicine and diagnostics (see below). The project is titled: Causes and consequences of whole-body composition using imaging, genetic, proteomic, and metabolomic data.

We are now looking for a doctoral student for the DDLS research school.

Duties 
The overall goal is to study how body composition, in various organs and tissues, is related to diabetes and cardiovascular diseases. This will be achieved by using detailed imaging, genetic, proteomic, and metabolomic data, collected for example the UK Biobank and SCAPIS studies, and by combining data-driven image analysis with multi-omics and genetic analyses of causality. The project will develop and apply image analysis methods that integrate image and non-image data for the mentioned large-scale studies.

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

- hold a Master’s (second-cycle) degree in an area relevant to the PHD topic (see below), 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.

For this position, the applicant must hold a master's degree in molecular biotechnology, bioinformatics, computer science, or another area that the employer deems relevant for the doctoral position. Good knowledge of English in both speech and writing is a requirement. The applicant must be able to teach in English.

Additional qualifications
A strong background in biology, programming or mathematics is meritorious. Knowledge in medical image processing, image registration, and large-scale analyses of genetic (including Mendelian randomization), protein, or metabolite information is also meritorious for this position.

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

General Description of the DDLS Program 
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 (about 290 MUSD) over 12 years from the Knut and Alice Wallenberg (KAW) Foundation.

In 2025 the DDLS Research School will be expanded with the recruitment of 19 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!

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.

Applications are received via the university's electronic recruitment system. It should include a CV, copies of diplomas and grades, any publications, and a brief description of your research interests. We welcome you to provide information about references and/or attach recommendation letters.

Regulations for doctoral students can be found in the Higher Education Ordinance Chapter 5, Sections 1-7, and in the unversity's rules and guidelines.

About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. The scope of employment is full-time, 100 %. Starting date as soon as possible or as agreed. Placement: Uppsala

For further information about the position, please contact: Professor Joel Kullberg, joel.kullberg@uu.se

For employment questions, contact HR Coordinator Higran Saghir, higran.saghir@uu.se.

Please submit your application by the 19th of April 2025, UFV-PA 2025/1241.

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