Job opportunities

  Software Engineer in Computational Bioscience

The Department of Pharmacology has an opening for a full time Professional Research Assistant.  This is full time* position in the Center for Computational Pharmaclogy in the Department of Phramacology at the University of Colorado Health Sciences Center.  The software engineer will work within a team of researchers to develop innovative data integration techniques for the analysis of high throughput genomic studies; a key component of which is the implementation of biomedical text mining systems.  We are lookiing for a team player with strong software development skills and an interest in the biomedical domain to join a cutting-edge bioinformatics research group.

Job Responsibilites:  Primary duties will center on the coding, testing, and documentation of a state-of-the-art biomedical data integration system.  Application development will be guided by user studies and client feedback.  This position will be responsible for implementing new functionality and maintaining a production-ready product.

Required Qualifications: This position requires a Bachelor's degree in computer science or a related discipline with a minimun of two years of object-oriented programming experience using Java.  Excellent verbal and written communication skills are required.  The ideal candidate will be capable of working as a member of a highly interdependent group of researchers, will be comfortable working with very large data sets and Semanitic Web technologies (in particultar RDF stores) and will have experience in parallel computing.

Preferred Qualifications:  Software testing expereience particularly with JUnit, Sun certification in Java 5 or greater.  Knowledge of biology, bioinformatics, linguistics, and/or text mining.  Experience with the Apache Unstructured Information Management Architecture (UIMA), JDBC, SQL, XML, RDF, Semanitc Web technologies, Protege, Apache Ant, and Eclipse.

*Part time employment may be a possibility.

TO APPLY: Send to Kathy.R.Thomas@ucdenver.edu a cover letter, curriculum vitae, and a statement of research interests; also arrange for three letters of recommendation to be sent to the same email address.

UC Denver is an equal opportunity employer.  Women and minorities are especially encouraged to apply.

Postdoctoral Fellowship in Computational Bioscience

The Computational Bioscience Program at the University of Colorado, Denver School of Medicine is recruiting to fill two NLM (NIH) funded postdoctoral fellowships.  The Computational Bioscience Program is home to seven core faculty working in the areas of genomics, text mining, molecular evolution, phylogenetics, network analysis, statistical methods, microarray, biomedical ontology, and other areas.  The School of Medicine is home to a broad array of outstanding research and instrumentation, including a 900 MHz NMR, extensive DNA sequencing and microarray facilities, and more.  We are housed on the first all-new medical campus of the 21st century, close to both the urban amenities of Denver and the beautiful Rocky Mountains.  For more information, please consult http://compbio.uchsc.edu

QUALIFICATIONS: Candidates must have a Ph.D. degree in Computational Biology or a related discipline, and be U.S. Citizens or Permanent Residents.

SALARY/BENEFITS: Successful candidates will be offered the NRSA specified stipend (based on years of experience), medical insurance, $2000 per year in travel support and $6500 per year in additional research-related expenses.

TO APPLY: Send to Kathy.R.Thomas@ucdenver.edu a cover letter, curriculum vitae, and a statement of research interests; also arrange for three letters of recommendation to be sent to the same email address.

UC Denver is an equal opportunity employer.  Women and minorities are especially encouraged to apply.

Postdoctoral positions available in

MIT Computational Biology group

The MIT Computational Biology group (compbio.mit.edu) is seeking highly motivated postdocs to undertake exciting new projects in computational and regulatory genomics.  We seek applicants with a strong background in machine learning, algorithm development, statistical methods, and their applications to computational biology, gene regulation, epigenomics, and integration of large-scale biological datasets.

Our group is part of the MIT Computer Science and Artificial Intelligence Lab, and of the Broad Institute of MIT and Harvard, leading to a truly interdisciplinary environment.  We have numerous ongoing collaborations with experimental and biological groups, and are part of the NIH ENCODE, modENCODE, and Epigenome Roadmap collaborative projects where our group plays a leadership role in data analysis and integration.

For more information about the group, please visit:  http://compbio.mit.edu/

Applicants are sought for the following ongoing projects:

(1) Integrative analysis of genomic and epigenomic datasets in the human genome, in the context of the NIH Epigenome Roadmap and ENCODE projects. Goal is to use many chromatin marks in multiple cell types in order to discover and interpret chromatin states, understand their biological roles, and their dynamics in differentiation and disease (NIH RC1-HG005334, NIH U54-HG004570).

(2) Integrative analysis of the Drosophila modENCODE project. Goal is to systematically understand the functional elements encoded in the fly genome, and the regulatory logic defining transcription factor binding and chromatin domains, and guiding developmental programs (NIH RC2-HG005639, NIH U54-HG004555).

(3) Regulatory genomics in human and fly genomes. Goal is to discover regulatory motifs, enhancers, and cis-regulatory modules in the human and fly genomes, and develop predictive models of gene regulation using comparative genomics and large-scale experimental datasets (NIH R01-HG004037).

(4) Role of non-coding RNAs in chromatin. Goal is to understand the role of small and large non-coding RNAs in directing, establishing, and maintaining chromatin modifications in human embryonic stem cells and during differentiation and cancer (Collaborative work with Ron Hart at Rutgers and John Rinn at HMS).

(5) Additional projects are available in comparative genomics, genome interpretation, microRNA regulation, phylogenomics, image analysis, RNA structure, and applicants are welcome to define their own projects within the context of ongoing activities in the group (NSF 0644282, NIH U01-HG004264, NSF 0936234).

For more information about open positions, please visit:

http://compbio.mit.edu/positions.html   or contact Prof. Manolis Kellis directly at <manoli@mit.edu>.