PhD Student in Advanced Data Analysis for Precision Oncology
Join Lund University as a PhD student to develop cutting-edge AI and computational tools for multimodal data integration and precision cancer medicine.
Best for:Best for aspiring computational biologists and bioinformaticians with a strong background in AI-driven image analysis and genomic data science.
Overview
Lund University is recruiting a full-time doctoral student to drive innovative research in precision oncology by integrating advanced molecular and imaging data. Working within a collaborative multidisciplinary group, the candidate will focus on developing computational and artificial intelligence methods to improve diagnostics, prognostication, and treatment selection for breast and prostate cancer. The role involves managing high-dimensional datasets from liquid biopsies, DNA sequencing, spatial single-cell technologies, and histopathological imaging. The successful applicant will initiate and execute independent research under supervision, contribute to scientific publications, and engage in translational clinical collaborations.
What you'll do
- Develop software infrastructure and analytical workflows for advanced biomedical data analysis.
- Design methods to integrate diverse sequencing-based DNA datasets for metastatic cancer studies.
- Build computational models for cancer prognosis and treatment outcome prediction.
- Analyze and integrate spatial single-cell gene and protein expression profiles.
- Create AI-based image analysis pipelines for histopathological specimens and whole-slide imaging.
- Contribute to manuscript writing, scientific publications, and conference presentations.
- Participate in grant writing and research funding applications.
Requirements
Degree required: Master's degree in Bioinformatics, Computational Biology, or equivalent (at least 240 ECTS credits, with 60 ECTS credits at an advanced level)
Degree offered: PhD
Language: English; strong spoken and written proficiency
Instruction: English
- Demonstrated experience in working with artificial intelligence models for image analysis
- Hands-on experience with sequencing-based DNA data analysis
- Proven ability to work independently and collaboratively with clinical researchers
- Familiarity with spatial single-cell technologies and workflows
Funding & terms
How to apply
Interested candidates should review the application portal requirements and submit their complete application package before the closing date. Ensure all requested academic credentials and supporting documents are properly uploaded.
- CV
- Degree transcripts
- Cover letter
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