Difference between pages "Research Interests" and "Postdoctoral Positions Available"

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(Created page with "The ultimate goal of our research is to understand how genomic DNA sequence specifies gene regulation. We are currently focused on 1) developing computational tools to identify f...")
 
 
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The ultimate goal of our research is to understand how genomic DNA sequence specifies gene regulation. We are currently focused on 1) developing computational tools to identify functional regulatory elements in non-coding DNA, and 2) experimentally testing and characterizing how these elements function.
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<h3>Postdoctoral Fellowship in Computational Genomics at Johns Hopkins University </h3>
  
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In our computational work, we are using microarray gene expression data, genome-wide location analysis, and whole-genome DNA sequence to systematically identify DNA functional elements and infer combinatorial regulatory logic. We use pattern recognition algorithms to identify over-represented and phylogenetically conserved DNA sequence elements (or putative transcription factor binding sites). We then use a probabilistic Bayesian network to find the most likely functional constraints on the position, spacing, orientation, and combinations of these DNA sequence elements. This methodology has generated a large set of high confidence predictions for regulatory interactions, and is in principle applicable to any organism with microarray and genome sequence data.
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A postdoctoral position is available in the Department of Biomedical Engineering, Johns Hopkins University School of Medicine to work with Dr. Michael Beer to develop novel computational models at the forefront of regulatory genomics as part of the ENCODE project.  Our laboratory actively analyzes and collaborates to generate functional genomic data (DNase-seq, ATAC-seq, MPRA, RNA-seq, Hi-C) to unravel the underlying DNA sequence code which specifies cell-type specific enhancer activity and regulatory contributions to a wide range of human diseases. Our lab is housed in the Institute of Genetic Medicine which provides a highly collaborative and dynamic environment and opportunities to directly evaluate and inform our computational models. For more details on our research see www.beerlab.org.
  
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In our experimental work, we are testing these computational predictions by rapid generation of transgenic GFP reporter strains in C. elegans via microparticle bombardment. C. elegans is an attractive model system for several reasons:
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<h5>Qualifications:</h5>
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1) The ideal applicant should have a PhD degree and publication record in computational biology, genomics, biomedical engineering, applied mathematics or physics, or other related fields with strong quantitative training.  
  
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* Relevance to human disease: About 60% of C. elegans genes have a human homologue (Harris et al., NAR 2004); and 80% of genes implicated in human cancer have a worm homologue (Futreal et al., Nat Rev Cancer 2004; Poulin et al, Oncogene 2004).
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2) Strong programming skills in C/C++, Python, or equivalent are required.
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* The high quality of the genome sequence data and microarray tools.
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* Rapid and effective transformation techniques and GFP reporter assays.
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Interested applicants should email curriculum vitae and at least three letters of recommendation to Dr. Michael Beer (mbeer@jhu.edu). Applications will be considered until the position is filled. The Johns Hopkins University is an Affirmative Action / Equal Opportunity Employer. There are no citizenship restrictions.
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* Availablity of bacterial feeding library for genome wide RNAi screens to further characterize regulatory interactions.
 
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* Relative ease and cost of strain maintenance.
 

Latest revision as of 03:32, 10 December 2016

Postdoctoral Fellowship in Computational Genomics at Johns Hopkins University

A postdoctoral position is available in the Department of Biomedical Engineering, Johns Hopkins University School of Medicine to work with Dr. Michael Beer to develop novel computational models at the forefront of regulatory genomics as part of the ENCODE project. Our laboratory actively analyzes and collaborates to generate functional genomic data (DNase-seq, ATAC-seq, MPRA, RNA-seq, Hi-C) to unravel the underlying DNA sequence code which specifies cell-type specific enhancer activity and regulatory contributions to a wide range of human diseases. Our lab is housed in the Institute of Genetic Medicine which provides a highly collaborative and dynamic environment and opportunities to directly evaluate and inform our computational models. For more details on our research see www.beerlab.org.

Qualifications:

1) The ideal applicant should have a PhD degree and publication record in computational biology, genomics, biomedical engineering, applied mathematics or physics, or other related fields with strong quantitative training.

2) Strong programming skills in C/C++, Python, or equivalent are required.

Interested applicants should email curriculum vitae and at least three letters of recommendation to Dr. Michael Beer (mbeer@jhu.edu). Applications will be considered until the position is filled. The Johns Hopkins University is an Affirmative Action / Equal Opportunity Employer. There are no citizenship restrictions.

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