Are you ready to take your passion for cancer genomics and data science to the next level? The Sun Lab at the University of Minnesota is looking for a highly-motivated Post-Doctoral Associate to join our cutting-edge research team. This is your opportunity to dive deep into cancer data science, focusing on genomic diversity and clonal evolution in tumors, and work alongside experts in bioinformatics, genomics, and cancer modeling.

About the Lab

At the Sun Lab, we’re on a mission to better understand tumor heterogeneity (ITH) and its role in cancer evolution. Our work bridges the gap between genomics and mathematical modeling, enabling new insights into the genetic basis of tumorigenesis. We are developing computational tools to model somatic copy number aberrations and clonal evolution, providing novel perspectives on cancer development. We collaborate with experimental biologists, clinicians, and mathematical oncologists to maximize the impact of our work.

For more information about our work and vision, visit our website: Sun Lab.

Your Role

As a Post-Doctoral Associate in Cancer Data Science, you will have the chance to work on innovative research projects, such as:

1. Modeling Cancer Evolution: Focus on the copy number and clonal evolution in cancer using computational methods.
2. Quantifying Intra-Tumor Heterogeneity (ITH): Develop techniques for analyzing and visualizing ITH from Next-Generation Sequencing (NGS) data.

You will be involved in:

• Conducting computational experiments for cancer genomics research.
• Designing and refining mathematical models to predict clonal evolution and the genetic landscape of tumors.
• Collaborating with a multidisciplinary team of researchers and clinicians.
• Mentoring opportunities for career development in areas like grant writing, project management, and teaching.

What We’re Looking For

Required Qualifications:

• A doctoral degree (Ph.D.) in Genetics, Bioinformatics, Computer Science, Biostatistics, Biomedical Engineering, Applied Mathematics, or a related field.
• Strong motivation and interest in cancer genomics and the modeling of clonal dynamics.
• Proficiency in script language programming (e.g., R, Python, Matlab, Julia).
• Excellent communication skills, both written and verbal.

Preferred Qualifications:

• Experience in cancer genomics or related fields.
• Knowledge of stochastic process models and their application to cancer research.
• Background in population genetics or statistical learning.

Why Join Us?

• Cutting-Edge Research: Join a forward-thinking team dedicated to advancing cancer research through data science and computational modeling.
• Career Development: Receive tailored mentoring and training in areas like grant writing, research design, and collaborative leadership.
• Impactful Work: Contribute to transformative projects that may change the way we understand and treat cancer.
• Collaborative Environment: Work in a dynamic, interdisciplinary team of researchers, clinicians, and computational biologists.