Post Doctoral Fellow - Emory University
Atlanta, GA 30322
About the Job
Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future. We welcome candidates who can contribute to the diversity and excellence of our academic community.
Description:The laboratory of Dr. Jacob Berchuck at the Emory University School of Medicine and Winship Cancer Institute is seeking candidates for an open postdoctoral research position. We are seeking a highly motivated individual who is interested in developing and implementing innovative laboratory and computational approaches to study the genetics and epigenetics of cancer from tumor and liquid biopsies. Candidates who are excited about liquid biopsy research and large/complex ‘omics’ data analysis of cancer (epi)genomes are encouraged to apply.
Bridging the realms of clinical oncology and laboratory science, the Berchuck Lab employs a “bedside-to-bench-to-bedside” research model, collecting tissue and blood samples from patients, applying cutting-edge research tools to characterize tumor molecular profiles, and translating discoveries into clinical practice. Our research predominantly focuses on “liquid biopsies,” working towards a future where a simple blood draw can provide real-time insights to select the right treatment for the right patient at the right time.
If you are an aspiring academic scientist looking to expand your skills and knowledge base, joining our team could be the perfect opportunity. Opportunities for career growth, authorship, and inventorship should be expected within our lab. You will have the chance to work directly with Dr. Berchuck, receive training in novel research techniques, lead independent projects, and engage in multidisciplinary collaborations. Our team operates as a highly functional and independent unit in a high-paced environment. You will have a chance to contribute to the current successful body of work: [pubmed] Each member takes ownership of their specific role, and together, we will bridge the gap between research and patient care.
Responsibilities:
We work in an interdisciplinary team environment with many local and external experts. All of our projects involve partnering with investigators who have diverse expertise in molecular and experimental biology, cancer biology, computational biology, and clinical research. The successful candidate will have the opportunity to work on transformative and leading-edge research problems in cancer research:
- Liquid Biopsy Analysis – develop and deploy novel laboratory and computational methodologies for utilizing liquid biopsies to study cancer and advance precision oncology
- Tumor Molecular Profiling – study tumor evolution, mechanisms of therapeutic resistance, non-coding genome alterations, cell plasticity, metastatic disease
- Multi-omic Data Integration –using genome, transcriptome, methylome, and chromatin/epigenetic data to study cancer subtypes, phenotypes, heterogeneity, and resistance to therapy.
Qualifications:
Minimum Qualifications:
- Applicants must have a PhD and/or MD (or equivalent) with training in one of these disciplines: molecular biology, cancer biology, computational biology, bioinformatics, computer science, data science, statistics, computer/electrical engineering, physics, or other related fields
- Applicants must have a demonstrated publication track record
- Works well in team environments, has strong communication/organization skills and is detail-oriented
- Highly motivated individual who thinks independently but also enjoys working in a dynamic, collaborative, multidisciplinary team
Preferred Qualifications:
- Experience with cancer data analysis and/or analyzing (epi)genomic sequencing data
- Programming experience (R, Python, Matlab, Java, C/C++, Perl or other languages for research)
- Candidates with interest and/or expertise in any of these research areas are highly encouraged to apply:
-- Cancer (epi)genomics, liquid biopsies, tumor evolution/heterogeneity
-- Application of statistical modeling, algorithm design, machine learning to study cancer and genetics
-- Analysis of large, complex (epi)genome and transcriptome data
**Please kindly attach a cover letter with your resume**
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