PhD Positions at the Center for AI in Radiation Oncology in (pediatric) digital oncology

PhD Positions at the Center for AI in Radiation Oncology in (pediatric) digital oncology

Entry Spring 2025 or upon agreement temporary for 4 years

The new Center for AI in Radiation Oncology (CAIRO) within the Inselspital and affiliated with the University of Bern will investigate data-driven solutions for radiation oncology applications in the context of outcome predictions, treatment personalization, and multi-modal learning. At the core of our research is the collaboration across disciplines spanning expertise in medicine, biology, computer, and data science. As part of the new group and with the support of the SNSF Starting Grant we seek four motivated PhD students to join this growing team and contribute to interdisciplinary research partnerships. The anticipated start date is spring 2025. Be part of a newly formed team that will start in the spring of 2025! Located in the heart of the Bern medical hub, the CAIRO research lab led by Sarah Brüningk invites applications for PhD positions to investigate data-driven solutions harnessing longitudinal imaging (MRI, CBCT), histopathology data, and digital pathology platforms and learning from multi-modal data such as multi-omics. The CAIRO aims to establish clinically deployable solutions and hypothesis generation to motivate clinical trials to close the loop between research and patient care. Specifically, we are working as a multidisciplinary team, ideally seeking applicants interested in biomedical data science applications and a strong computational background. The anticipated projects span: 1) Computer vision applications for (pediatric) brain tumor response prediction and modeling of tumor growth and recurrence in a mechanistic learning framework paired with an investigation of data harmonization through generative models. Prior knowledge in generative modeling on imaging, image segmentation, and generally computer vision is key. 2) Digital Pathology solutions for in silico characterization of the tumor microenvironment. Building on a unique dataset comprising spatial proteomics and histopathology we aim to investigate digital pathology solutions for tumor subtyping and characterization at high spatial resolution. Prior knowledge of large-scale data handling and computer vision is preferable. 3) Foundation models for multi-omic data integration, representation learning, and response prediction. Building on combined data from transcriptomics, whole genome sequencing, methylation, and copy number variation we aim to model different aspects of response to radiotherapy, radiosensitization, and systemic therapies. A background in mechanistic modeling in addition to a general understanding of the involved data types is a plus. 4) Learning from diverse multi-modal data (imaging and pathology/omics data integration) aiming for the prediction of patterns of therapy response and resistance at the patient level. A PhD position within the CAIRO offers an excellent opportunity to work at the forefront of biomedical data science and computer vision on multimodal data, contributing to both radiation oncology and data science research alike. Given the variety of proposed projects, we are keen to work with the selected candidates to tailor specific projects in the context of joint interests and applications.

• Data curation, cleaning, and preprocessing: Support the curation, cleaning, and harmonization of biomedical datasets, handling of databases, and optional workflow integration.
• Develop and implement ML/DL models to analyze (multi-modal) data - an innovative approach building on recent theoretical advancements is desired
• Design and validate predictive algorithms for (imaging) biomarker discovery
• Optimize data integration techniques for multi-omics and clinical datasets
• Communicate with clinical experts regarding the requirements for data preparation and feature extraction
• Prepare manuscripts, and presentations to disseminate findings
• Be part of an engaging and collaborative team

• You have a Masters degree in a relevant field such as data science, computer science, medicine, physics and/or biomedical research
• You are proficient in Python programming with experience in the implementation of machine and deep learning models - depending on the project you apply for you further bring expertise in computer vision, digital pathology, or the processing of molecular data
• You have experience in software development including collaborative coding, version control, and the use of compute clusters
• You ideally have a background in biomedical projects with experience in interdisciplinary collaboration
• You are motivated to work as part of a team and strive towards scientific excellence in your field
• You are proficient in English in writing and speaking

We offer a 4-year PhD position at the Faculty of Medicine of the University of Bern, 100%, based on SNSF salary bands, that includes:

• Opportunities to engage with different communities bridging data science and biomedical research leading to high-impact publications and research projects tailored to make a difference for our patients
• You will be part of a highly motivated, multidisciplinary, and collaborative team
• You will collaborate with leading national and international teams
• We encourage the attendance of relevant (inter-) national conferences to increase your visibility and present the project outcomes
• You can be involved in the supervision of junior researchers and optional teaching in the lab
• Access to state-of-the-art computational resources and collaborative research networks as part of an AI Center directly embedded in a clinical environment
• Opportunities for professional development and career advancement