Job description: Two computational postdoctoral level positions (postdoc fellow or research scientist) are available at the Mount Sinai School of Medicine (Top-20 medical school in the US) in New York City. Our humid lab (80% computation + 20% wet lab) is in the department of Genetics and Genomic Sciences and the Institute for Genomics and Multi-scale Biology, one of the top institute on computational biology in the nation (http://icahn.mssm.edu/departments-and-institutes/genomics). Our lab emphasizes biological and biomedical impacts in the design of computational, experimental, statistical and integrative methods. Successful candidates will have unique opportunities to i) build on our unique expertise and momentum of 6mA epigenomics, and a strong network of collaborators, ii) synergize effective computational design with innovative experimental design, iii) take the lead role in multiple projects on the innovative use of third-generation sequencing and systems biology to better understand basic biology (bacteria, lower eukaryotes and mammals), human diseases and personalized medicine, not just for high-profile publications but also for the development of your own unique and competitive expertise and career path. Compensations for successful postdoc fellows are highly competitive. All employees are eligible for medical, dental, and health insurance. Subsidized housing is available for postdoctoral fellows.
Research problem: Although cytosine methylation (5mC) has been almost exclusively studied as the DNA methylation in human, methylation of other nucleotides exist across all kingdoms of life. Specifically, methylation of adenines (e.g. 6mA) is most prevalent in bacteria, and it also exists in eukaryotes. Recent work by us and others discovered that 6mA has significant functional roles in the regulation of core biological processes (e.g. cell cycle, gene expression, DNA repair etc.) in both prokaryotes (pathogenic bacteria, infectious diseases, antibiotic resistance) and eukaryotes (pathogens, model organisms and mammals). The research goal and focus of our humid lab is to explore this young and promising field of 6mA epigenomes, its relationship to 5mC epigenomes and histone modifications, and make fundamentally new discoveries of novel regulatory mechanisms and more effective drugs.
Unique expertise: We pioneered the fast growing field of bacterial epigenomics (6mA, 4mC and 5mC), focusing on pathogens that cause infectious diseases and associated cancers (especially interested in multi-drug resistance and virulence prediction). We have unique expertise in the use of third generation sequencing (single molecule real-time, ~20kbp read length, and the emerging nanopore technique) with advantages of detecting >20 different types of DNA modifications, single molecule-level epigenetic phasing, full-length gene isoforms, complex structural variations, beyond second-generation techniques, in prokayotes and eukaryotes. We integrate third-generation and second-generation sequencing for functional/comparative epigenomics/genomics and transcriptomics.
Recent publications on these topics include:
- Nature Communications, 2015
- PLoS Genetics, 2015
- Biological Psychiatry, 2015
- Nature Communications, 2014
- Molecular Psychiatry, 2014
- PLoS Genetics, 2013
- PLoS Computational Biology, 2013
- Nature Biotechnology, 2012
- Genome Research, 2012
Lab page with details: http://research.mssm.edu/fanglab
Interested? Excited? Join us to reveal the cool biology! Candidates with PhD in computational biology, bioinformatics, computer science, or statistics with experience on analyzing biological and medical data are encouraged to apply. Solid computer programming, statistical, data mining, machine learning skills are desirable. Please send the following to fanggang@gmail.com
- CV with a list of publications
- PDF files for the papers that involve computational and statistical data analyses, in which you are first or co-first author.
Thank you for the interests!
Gang
P.S. Key words (without ordering): Epigenomics, DNA methylation, DNA modifications, personalized medicine, translational research, genome assembly, genome-wide association datasets, data integration, network biology, protein interaction, regulatory networks, eQTL, brain imaging, structural and functional MRI, data mining, mental disorders, neurodegenerative diseases, cancers, pathogen-host interaction, epistasis, genetic interactions, functional genomics, comparative genomics, microbiology, combinatorial, statistics, machine learning, bioinformatics, human induced pluripotent stem cell, gene expression, RNASeq, mitochondrial DNA, bacterial virulence, antibiotic resistance, drug design, next generation sequencing, third-generation sequencing, single molecule real-time sequencing, C/C++/Java, perl/python, Matlab/R, Microbiology, GWAS, data mining, machine learning, biological networks, large scale data analysis, Big data, metagenomics, metatranscriptomics, meta-genomics, meta-transcriptomics.
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