**Job Description**
Professor Florian Markowetz seeks a highly motivated PhD student to develop and apply computational tools for the early detection and deconstruction of chromosomal instability (CIN) in cancer. The project builds on previous work in developing computational methodologies to detect and deconvolute mutational processes associated with CIN, leveraging single-cell DNA sequencing for CIN heterogeneity, and implementing machine learning and AI models for imaging data. The student will develop new models for early CIN cancer detection, apply advanced computational and machine learning approaches to improve understanding, and build models to enhance patient survival and treatment outcomes. The project allows the applicant to focus on cancer genomics methods or early detection in imaging, with opportunities for cross-cutting research combining both areas.
**Skills & Abilities**
• Strong analytical skills
• Desire to develop novel computational methods and ML/AI tools
• Highly motivated and independent
**Qualifications**
Required Degree(s) in:
• Computational Biology
• Mathematics
• Computer Science
• Relevant Biological degrees with sufficient computational background
Minimum Degree Requirement: First/Upper Second Class degree (or equivalent) from any recognised university worldwide.
**Experience**
Experience Required:
Other:
• Relevant research experience (e.g., Master’s study or laboratory work) is strongly encouraged
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