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Post-Doctoral Research Fellow – Cancer Genomics
November 19, 2018 - December 21, 2018
A postdoctoral position in the laboratory of Dr. Gavin Ha and the Computational Biology Program is available immediately. We are seeking a highly motivated individual who is interested in studying cancer and understanding the genetic and epigenetic basis driving cancer progression. Candidates who are excited about large/complex ‘omics’ data analysis and methods development for cancer research are encouraged to apply. The position has a duration of at least one year with a competitive salary and great benefits.
The Ha lab is establishing a research program that uses new DNA sequencing technologies to study cancer genomes. The lab is also focused on research involving liquid biopsies, such as cell-free DNA, and developing new computational approaches to leverage these data for genome discovery and cancer burden monitoring. The research interests/projects in the Ha lab include:
- Analysis of cancer genomes to understand tumor progression/evolution, metastatic disease, non-coding genome alterations, copy number alterations, genome rearrangements and 3D structure, mutational signatures
- Development of novel computational algorithms for long-range (linked-reads or long-reads) whole genome sequencing of tumors
- Analysis of linked-read whole genome sequencing data to uncover novel alterations driving metastatic prostate cancer
- Analysis of cell-free DNA in plasma samples from patients under treatment
- Development and analysis of sensitive approaches to detect tumor-derived DNA in cell-free DNA from patient blood plasma
- The lab will work with collaborators to validate results using functional experiments
- For examples of recent studies, see PMID:29909985, PMID:29109393, PMID:25060187
- https://gavinhalab.github.io/
Candidates with strong interest and/or expertise in any of these research areas are highly encouraged to apply
- Cancer genomics, liquid biopsies, tumor evolution/heterogeneity
- Application of statistical modeling, algorithm design, artificial intelligence to study cancer and genetics
- Analysis of large, complex genome, epigenome, or transcriptome data
Qualifications
Applicants must have a PhD in one of these disciplines: Computational biology, bioinformatics, computer science, data science, statistics, computer/electrical engineering, physics, or other related fields
Applicants should have some of the following skills and experience:
- Work well in team environments; strong communication/organization skills; detail-oriented
- Strong programming experience (R, Python, Matlab, Java, C/C++, Perl or other languages for research)
- Experience with high performance computing environments and cloud computing environments is a plus
- Experience with analyzing sequencing data is considered a strong asset
- Applicants must have a demonstrated publication track record.
- A background in cancer biology (esp in prostate or breast cancer) is considered a strong asset.