Two Postdoctoral Researchers in Mathematical and Computational Oncology for Personalized Breast Cancer Treatment

We are seeking two ambitious Postdoctoral Researchers to join the Köhn-Luque group at the Oslo University Hospital. These 3-year positions are part of a high-impact project funded by the Norwegian Cancer Society titled “Precision biomarkers for CDK4/6 inhibition in breast cancer”. Start date: Negotiable (immediate preference).

About the project: The core objective is to develop, validate and initiate clinical translation of precision biomarkers for CDK4/6 inhibitors in breast cancer. Following previous work from Köhn-Luque’s group (Schmiester et al. Clin Cancer Res 2024; Lai et al Cancer Res 2019), we plan to integreate extensive preclinical and clinical data with mechanistic mathematical modeling and machine learning to deliver personalized treatment recommendations.

The candidates will join a multidisciplinary research team at the Department of Medical Genetics at the Oslo University Hospital. In addition, they will collaborate with researchers and clinicians in different institutions in Norway and abroad, including Integreat: The Norwegian Centre for Knowledge-driven Machine Learning, the Akerhus University Hospital, northeast of Oslo, and the Clinic Hospital in Barcelona. The candidates will also be involved in a SPARK Norway innovation project that is exploring the commercial potential of mathematical and computational biomarkers.

The Department of Medical Genetics at Oslo University Hospital is Norway’s largest medical genetics department with over 200 employees. The department is responsible for diagnostics of rare and inherited diseases, and runs a national research infrastructure for high-throughput DNA sequencing at the Norwegian Consortium for Sequencing and Personalized Medicine. The research section in the department has several research groups working in various fields of medical genetics, including breast cancer, the genetics of autoimmune, neurological, cardiovascular and psychiatric disorders, epigenetics causes of disease, as well as groups focusing on mathematical modeling, artificial intelligence and bioinformatics. 

Integreat is a centre of excellence funded by the Research Council of Norway of the University of Oslo, UiT the Arctic University of Norway and the Norwegian Computing Center. Researchers in Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By combining the mathematical and computational cultures, and the methodologies of statistics, logic and machine learning in unique ways, Integreat's machine learning will solve fundamental problems in science, technology, health and society, and contribute to make Norway a world leading country in AI. 

SPARK Norway is the UiO: Life Science’s innovation programe within health-related life sciences. It provides mentoring, milestone-based funding and education to further develop promising ideas.

Job descriptions

Position 1: Mathematical Modeler in Oncology.

The focus is on modeling and simulating underlying biological mechanisms of drug response. Main tasks include but are not limited to:

• Model development: Construct and refine mechanistic mathematical models (predominantly systems of ODEs) that describe the pharmacodynamics of CDK4/6 inhibitors and interaction with other targeted therapies.
• Data management: Curate, analyze and maintain molecular and clinical datasets
• Data integration: Perform sophisticated calibration and parameter estimation using high-dimensional longitudinal data, including transcriptomics and proteomics.
• Predictive Simulations: Use validated models to perform in silico trials, identifying optimal dosing schedules and resistance-evading combinations.

Position 2: Machine Learning Researcher in Oncology.

The focus  is on integrating machine learning and mechanistic modeling to discover underlying biological mechanisms from data. Main tasks include, but are not limited, to:

• Model learning evaluation: Conduct rigorous evaluations of model learning approaches for noisy and high-dimensional data.
• Hybrid frameworks: Extend hybrid machine learning frameworks (e.g., Universal Differential Equations, Universal Physics-Informed Neural Networks) to represent unknown biological pharmacodynamics from multi-omics data.
• Interpretability: Discover parsimonious mathematical expressions from omics data using symbolic regression, specifically to understand how interpretable biomarkers enter and govern the functional forms of mechanistic models.
• Benchmarking: Establish rigorous pipelines to compare the predictive performance of hybrid and symbolic models.

The physical working location will be at the Department of Medical Genetics, Section for Research and Development. From January 2027, the Department will move to the Life Science building, providing the applicants the exciting opportunity to work in Norway’s largest and most modern research building.

Qualifications

Education: A PhD in Mathematics, Statistics, Physics, Computer Science, Computational Biology, or a related quantitative field. The PhD degree must be obtained by the start date.
Computational expertise: Extensive experience in scientific computing and software development. The candidate must demonstrate the ability to develop and maintain code (Python, Julia, R, or C++)
Mathematical Modeling (Position 1): Deep theoretical and practical expertise in dynamical systems, numerical analysis of ODEs/PDEs, statistical inference, parameter estimation and optimization for systems biology modeling.
Machine Learning (Position 2): Strong theoretical and practical experience in machine learning, specifically in dynamical model learning methods (e.g., neural differential equations, symbolic regression).

• Experience with transcriptomics and proteomics data.
• Experience working on servers and/or in a HPC environment.

Personal qualities

• We are looking for a researcher who is highly motivated, well-organized and dynamic with a high level of independence and creative thinking.
• Ability to present and execute novel ideas in method development, data analysis and interpretation.
• Team player who can work independently in a multidisciplinary and international team.
• Excellent oral and written English communication skills.
• Proactive, flexible, and problem-solving attitude.
• Experience in working with deadlines and being involved in multiple projects.

We offer

• A 3-year full-time contract in a world-class research environment with possibility for extension, depending on the availability of funding.
• A 6 months trial period will be applied.
• Salary in agreement with the current collective agreement, and qualifications/experience.
• Favorable pension arrangements.
• A stimulating (international, multidisciplinary) research environment where quality, professionalism and team spirit are encouraged.
• A productive and motivating research environment.
• Attractive welfare arrangements.

• Applications only through "Webcruiter" are accepted.
• The application letter including a summary of scientific work and interest. Please, indicate you fit in Position 1, Position 2 or both.
• CV summarizing education, positions and other qualifying activity.
• Copies of educational certificates with grades.
• Names, email and telephone number of 3 referees (describe relation to applicant).
• A complete list of publications, highlighting the candidate’s role in main publications relevant to the position. 

• The Department of Medical Genetics: https://www.ous-research.no/meg/
• Norwegian Consortium for Sequencing and Personalized Medicine: https://www.norseq.org/
• Integreat: https://www.integreat.no/
• SPARK Norway: https://www.uio.no/english/research/strategic-research-areas/life-science/innovation/spark/
• Life Science building: https://www.uio.no/english/research/strategic-research-areas/life-science/about/building/ 

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