PhD Position in Bioinformatics and Machine Learning for RNA Fragmentomics in Cancer Diagnostics
Join MultiD Analyses AB and the University of Gothenburg for a unique PhD opportunity focused on developing innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through data-driven diagnostics. This collaborative project addresses the challenge of monitoring cancer treatment efficacy and early relapse detection by analyzing cell-free RNA in patient blood samples. The measurements aim to reveal disease status, tumor response to therapy, and inform treatment strategies.
The successful candidate will be employed by MultiD Analyses AB and split their time between MultiD at GoCo Health Innovation City and the University of Gothenburg, Sweden. The academic supervisor is Professor Anders Ståhlberg, with co-supervisors Dr. Martin Smelik and Professor Mikael Kubista. The project is conducted in close collaboration with partners across academia, industry, and healthcare.
Research activities include designing new statistical and machine learning models tailored to this emerging omics modality, working with high-dimensional datasets that combine quantitative RNA features, positional fragment data, and clinical variables, and applying methods in ongoing biological and clinical studies with the ambition of implementation in healthcare. The environment is highly collaborative, offering cross-sector research opportunities.
Applicants should be highly motivated PhD candidates excited by computational biology, biostatistics, bioinformatics, or data science, and eager to work at the intersection of data-driven life science, translational research, and cancer diagnostics. Methodological innovation and real biomedical applications are central to the project. Eligibility requirements include a completed degree at second-cycle level, or course requirements totaling at least 240 credits (with at least 60 credits at second-cycle level), or equivalent knowledge acquired in Sweden or abroad. Successful completion of English B/6 or equivalent knowledge through previous studies is required. Applicants should include a personal letter and CV with information about programming skills.
This position is part of the Data-Driven Life Science (DDLS) program, which combines data, computational methods, and artificial intelligence to study biological systems from molecular structures to human health and ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science aims to recruit and train the next generation of data-driven life scientists and create globally leading computational and data science capabilities in Sweden. In 2026, the DDLS Research School will expand with the recruitment of 25 academic and 7 industrial PhD students, joining a community of more than 260 PhD students and 200 postdocs. The DDLS program covers four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, and epidemiology and biology of infection.
For more information about the DDLS program and application instructions, visit the provided links. The future of life science is data-driven—be part of this change by joining this unique program!
