The Sun lab at the University of Minnesota is seeking a highly-motivated postdoc with a passion and perseverance for advancing cancer data science. The Sun Lab (https://ruping.github.io/) is located at the University of Minnesota on the Twin Cities campus. Our work stems from the rationale that one can quantify intra-tumor heterogeneity (ITH, or genomic diversity of cell populations) from patient tumor sequencing data and in turn, leverage the patterns of ITH to infer the mode (or the way) of clonal evolution in vivo. We strive to bridge ITH with mathematical modeling to delineate the roles of genomic aberrations in the development of patient tumors. For example, we are creating computational tools for yielding novel insights into the evolutionary trajectories and roles of somatic copy number aberrations during tumorigenesis (https://www.biorxiv.org/content/10.1101/2022.06.14.495959v1), and for connecting the genomic distance between longitudinal tumor samples with underlying evolutionary parameters through modeling (https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008838). We also maintain vigorous collaborations with experimental biologists, clinicians, and mathematical oncologists to maximize the impact of our work.
Example research topics are:
- Modeling of the copy number evolution and clonal evolution in cancer.
- Methods for quantifying and visualizing ITH from NGS data (including both bulk and single-cell sequencing);
Based on his/her training background, the person who holds this position will receive mentoring on different aspects that he/she would like to develop further and tailored training for career development. This includes but is not limited to grant writing, project design and management, and teaching skills. While the successful candidate is expected to get involved in the aforementioned research topics, his/her research interests will be encouraged and promoted under the general scope of the lab. For more information on the position, applicants may email Ruping Sun, Ph.D. (firstname.lastname@example.org).
All required qualifications must be documented on application materials.
- A doctoral degree in genetics, bioinformatics, computer science, biostatistics, biomedical engineering, industrial engineering, applied mathematics, biophysics, or other appropriate areas;
- Strong motivation in working in cancer genomics and modeling of clonal dynamics
- Script language programming skills (e.g., R, Matlab, Python, Julia);
- Written and verbal communication skills.
- Experience in cancer genomics, or
- Knowledge of models in stochastic processes, or
- Background in the study of population genetics, or
- Experience in the application of statistical learning
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