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Note: The job description below is from the "12/04/15 Jobs, Fellowships & Announcements of Interest for Duke Postdocs" email sent out weekly to the postdocs@duke.edu list-serv by Molly Starback.

Note: A recruiter has contacted me (Jason Belsky) regarding this position.  If anyone is interested, I can forward her information along.

Note: As of December 6, 2015, I cannot find this position on the synetics.com employment website.  Not sure if this means the position has already been filled, or if it just hasn't been officially posted yet.

Bioinformatics Scientists, Synectics Inc, RTP NC

At our headquarters in the Research Triangle Park in North Carolina, we are seeking Bioinformatics scientists within the Integrated Trait Knowledge Function. This position will directly report to the Bioinformatics team leader at RTP. The scientist will work locally and globally with other researchers, computational biologists and bioinformaticians in providing data analysis support. The work will involve analyzing next generation sequencing and large scale genomic and phenotypic data. We expect the scientist to be involved on one or more of currently ongoing projects on gene expression analysis, genome sequence analysis, assembly and annotations leveraging information and knowledge creation from diverse genomics datasets and computational tools. In addition, the scientist will gain experience working as part of a multifunctional project team within a global sub-function and exposure to how business strategy drives R&D work within a corporation.

Key responsibilities will include working in one or more of the following areas: curation and management of large datasets, gathering end user requirements developing, optimizing and applying pipelines and algorithms for processing and analyzing biological data conducting independent data analysis and interpretation and generating reports as per specifications evaluating tools and coordinating efforts between the project teams and IT groups to define, validate and implement software for data management and analysis.


  • PhD in Bioinformatics, Computational Biology, Molecular Biology or a related field with Bioinformatics analysis experience, MS with 2 years experience or BS with > 5 years experience. Computer Science and IT degrees with the related amount of experience in a biological field may be considered.
  • Background and experience working with one or more areas of: molecular biology, bioinformatics, computational biology, computer science; use of various bioinformatics and data analysis applications
  • Unix environment with basic to intermediate unix skills, be proficient in one or more programming languages (Perl, Python); data curation, database design and development; statistical analysis methods
  • Experience in one or more areas of computational biology is a plus: sequence related analysis, next generation sequence data analysis; gene sequence optimization; gene expression analysis, RNA-seq, microarray, proteomics; genome sequence analysis, assembly and annotation; metagenomics analysis; comparative and phylo-genomics; pathway and gene functional analysis; network analysis/modeling approaches; phenotypic data analysis; implementation of tools for genomic data integration and visualization
  • Knowledge of plant, fungal and microbial biology, molecular biology or genomics
  • Experience defining requirements and interpreting results for scientists

 For more information and to apply: http://www.synectics.com/employment.php

Duties and Responsibilities:
Two postdoctoral positions in statistical genomics are available in Dr. Audrey Fu's lab (http://webpages.uidaho.edu/audreyf/) in the Department of Statistical Science and the Institute of Bioinformatics and Evolutionary Studies (IBEST) at the University of Idaho in Moscow, Idaho. Both positions involve development of statistical methods and computational algorithms, with an emphasis on causal inference, for the analysis of high-throughput biological data in genomics, such as gene expression data from RNA-seq or microarray, protein binding data from ChIP-chip or ChIP-seq, and genotyping data, etc.

Position Qualifications:
The first position is for 3 years and has a focus in cancer genomics. The second position is for 2 years with the possibility of extension, and focuses on single-cell genomics. Both postdoctoral fellows will have the opportunity to interact with not only researchers in the Department of Statistical Science, but also members at the IBEST who have diverse backgrounds and work on various projects in genomics, population and evolutionary genetics. The postdoctoral fellows will be encouraged to attend and present their results at national or international conferences in related fields. They will also be encouraged to apply for their own funding if interested. The positions will offer competitive salaries and benefits.

The university is located in a college town and is close to Washington State University; the two universities collaborate in research as well as teaching. The area offers safe, affordable, healthy, and family-friendly living. The Palouse area is famous for its beautiful rolling hills, mountains and rivers, and provides plenty of opportunities for outdoor sports year round, such as hiking and skiing (see photos of this area here http://www.bbc.com/travel/story/20150629-saving-a-picture-perfect-americana).

Candidates will have a Ph.D. in bioinformatics, computational biology, genetics, statistics, computer science, math, or a related field. Ph.D. must be completed before position begins. A strong computational background is required. Candidates should have proficiency in at least one of the following programming languages: Perl or Python, C or C++, and R. Experience with commonly-used statistical and bioinformatics software and high-throughput sequencing data is helpful but not required. Knowledge in single-cell biology or cancer biology and experience with large cancer consortium data, such as TCGA and ICGC, are also helpful but not required. Application Information: Applicants should send a CV, a short research statement, and names of three referees to stat@uidaho.edu. Inquiries may also be sent to this email or to the PI at audreyf@uidaho.edu. Review of applications will begin immediately, and continue until the positions are filled. Additional info is available at the following URLs through the university human resources website:

Audrey Qiuyan Fu, PhD
Assistant Professor
412 Brink Hall
Department of Statistical Science
Institute of Bioinformatics and Evolutionary Studies
University of Idaho
Moscow, Idaho 83844-1104
Email: audreyf@uidaho.edu
URL: http://webpages.uidaho.edu/audreyf/

Check out the postdoc opportunity (https://postdoc.duke.edu/node/2373) below forwarded by Ashlee Valente, a CBB Alum (Graduated 2014)
Are there any CBB students graduating in the very near future who might be interested in a postdoc in CAGPM? It would be a lot of clinically relevant data analysis and some statistical modeling under the advisement of a new faculty member in ECE, Ricardo Henao. It should pay pretty well for a post doc (link below). If anyone wants more details they can feel free to contact me.
Ashlee Valente
Department: Duke Center for Applied Genomics & Precision Medicine, DOM
Job Description: 

The postdoctoral position will reside in the Duke Center for Applied Genomics & Precision Medicine within the Department of Medicine, under primary supervision by Dr Ricardo Henao and co-mentorship by Dr Ricardo Henao and Dr Geoffrey Ginsburg. The qualified candidate will work within applied genomic medicine programs focusing on development of novel statistical models and analytical methods from high-dimensional genomic and clinical datasets, including (RNA) sequencing data, microarray data, multiplex PCR data or other complex ‘omic’ datasets. The work may also extend to text mining and pathways analysis. This position is available for immediate hire with a 2 year term and opportunity for additional annual renewal contingent on performance and funding availability.   Additional Scope: The candidate will be expected to develop novel statistical and machine learning methodologies tailored to utilize the data generated by the Ginsburg lab and to address medical / translational problems. It is anticipated that there will be a wide variety of statistical and machine learning methodologies that are relevant to these problems. The candidate will need to be able to remain current in the literature in these fields and it is expected that s/he will spend at least 50% time researching and developing novel analysis methodologies. Remaining effort will be spent in collaborative work with physicians and biologists within the applied genomic medicine programs supporting refinement and interpretation of analytical results from biological and clinical studies and activities destined for publication. The candidate is expected to develop research results into quality manuscripts for submission to peer-reviewed journals, and for presentation at relevant scientific meetings or conferences.  The candidate is expected to participate in regular group or project team meetings, and present and discuss research results as necessary. The successful candidate will be an integral member of any team of investigators working on the genomics project(s) from which the data is derived.

Pratt PhD Plus Program

Check out the PhD Plus Program in the Pratt School: http://phdplus.pratt.duke.edu/content/how/overview

This looks to be a great career development model that hopefully will expand to the life science PhD programs in the near future.

Take a look at two articles describing the program: