PhD student in advanced data analysis for data integration, image analysis, and precision oncology

PhD Student In Advanced Data Analysis For Data Integration, Image Analysis, And Precision Oncology

Lund University was founded in 1666 and is repeatedly ranked among the world's top universities. The University has around 46 000 students and 8 500 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

The overarching goal of our research is to advance precision medicine by improving prognostication and treatment selection for cancer patients through the development of novel prognostic and treatment-predictive biomarkers, as well as by elucidating tumor biology to better understand mechanisms of treatment resistance and identify new therapeutic targets. To achieve this, we apply state-of-the-art technologies for molecular tumor analysis using both solid tissue and blood-based liquid biopsies derived from unique and well-annotated clinical cohorts. Our research integrates advanced liquid biopsy approaches, including analysis of circulating tumor cells and circulating tumor DNA, with comprehensive tissue-based profiling methods such as gene expression analysis, DNA sequencing, single-cell sequencing, and spatial transcriptomics. These high-dimensional data are analyzed using advanced bioinformatic and biostatistical methodologies.

As a doctoral student, you will be part of a highly collaborative and multidisciplinary research group focusing on developing precision medicine tools for better diagnosis and treatment of breast and prostate cancer. You will work closely with computational scientists, molecular biologists and clinical researchers in a translational setting.

The research is conducted within a highly supportive academic environment with excellent access to infrastructure and core facilities at Lund University, including platforms for genomics, transcriptomics, bioinformatics, and advanced imaging.

The research group is now recruiting a full-time doctoral student (100%) with a start date of 1 November 2026 (or as agreed).

The PhD student will be responsible for leading projects focused on the development of novel computational and AI tools to improve our understanding of multimodal data for precision oncology. The projects include integrating different types of sequencing technologies for cell-free DNA in metastatic prostate cancer, developing novel methods to analyze single-cell spatial transcriptomics and protein data in paired prostatectomy samples and lymph nodes in prostate cancer, and to develop a novel method to classify lymphovascular invasion in primary breast cancer from whole-slide histology imaging and gene expression data.

As a doctoral student, you will, under supervision, be responsible for initiating, conducting, and completing research projects in precision cancer medicine. In particular, your responsibilities will include:

• Advanced data analysis, including the development of software infrastructure to optimize data workflows
• Developing analytical methods to integrate different types of sequencing-based DNA data.
• Developing computational models for prognosis and treatment prediction
• Integrating various types of spatial single-cell data, such as gene expression and protein expression data
• Developing image analysis methods for histopathological specimens using AI-based models

  As a doctoral student, you will also, under supervision:

  • Contribute to various stages of the scientific publication process
  • Present scientific results in different forums
  • Apply for research funding

    Required Qualifications:

    • A background in Bioinformatics, Computational Biology, or equivalent (at least 240 ECTS credits, of which 60 ECTS credits are at an advanced level).
    • Experience working with AI models for image analysis
    • Experience working with sequencing-based analysis of DNA
    • Documented ability to work independently in close collaboration with clinicians and other researchers
    • Experience working with spatial single-cell technologies
    • Ability to communicate in English, both spoken and written.

      We expect you, as a person, to be meticulous and goal-oriented.

      Meritorious Qualifications are:

      • Advanced courses in data science or computational biology relevant for cancer research
      • Previous research projects using bioinformatic methods for cancer research, in particular development of novel tools for prognostic or treatment predictive biomarkers.
      • Previous experience of breast or prostate cancer research.
      • Previous experience working with liquid biopsies for cancer diagnostics.