<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: My posts on The Opportunity]]></title>
	<link>https://bioinformaticsonline.com/opportunity/owned/martin?offset=5</link>
	<atom:link href="https://bioinformaticsonline.com/opportunity/owned/martin?offset=5" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/19086/postdoctoral-fellowship-in-bioinformatics</guid>
  <pubDate>Sat, 08 Nov 2014 14:41:14 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral fellowship in Bioinformatics]]></title>
  <description><![CDATA[
<p>A two-year post-doctoral position is available in the Biocomputing group of the Sapienza University led by Anna Tramontano to work on either genomics research or structural bioinformatics, focusing on the study of relevant biomedical problems.<br />The ideal candidate should be motivated and talented, hold a PhD degree, have good programming skills, a grasp of statistical methods and an understanding of biology.<br />Experience in the development of computational biology methods would be an added value.</p>

<p>Good communication skills and fluency in spoken and written English are required.<br />Please apply sending a curriculum vitae, the names of at least two referees and a letter of motivation describing past experience and future goals to anna.tramontano@uniroma1.it with subject: “Application for post-doctoral position November 2014 YOUR LAST NAME”</p>

<p>Deadline: No later than November 28th, 2014.<br />Duration: 2 years</p>

<p>Salary on grant: Commeasured to the experience of the candidate<br />Contact Person (Referent): Anna Tramontano<br />Ref. E-Mail: anna.tramontano@uniroma1.it<br />Group Web Page: http:/www.biocomputing.it</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/18576/graduate-research-assistantships-university-of-nebraska-lincoln-unl</guid>
  <pubDate>Wed, 22 Oct 2014 10:05:31 -0500</pubDate>
  <link></link>
  <title><![CDATA[Graduate research assistantships @ University of Nebraska-Lincoln (UNL)]]></title>
  <description><![CDATA[
<p>Graduate research assistantships in quantitative genetics are available with Gota Morota in the Department of Animal Science at the University of Nebraska-Lincoln (UNL).</p>

<p>Current projects in the Morota lab include developing kernel-based whole-genome prediction and kernel-based genome-wide association models, polygenic modeling of binary traits, reexamining the results from quantitative genetics analysis in light of functional annotation, and extending kernel methods (such as GBLUP and RKHS) specifically tailored for diverse types of emerging omics data.</p>

<p>In addition, candidates will be expected to leverage opportunities to interact with faculty in animal genetics and biometrics at the UNL in the areas of bioinformatics, breeding, functional genomics, quantitative genetics, and molecular genetics.</p>

<p>Candidates should have a B.S. or M.S. degree in quantitative disciplines with strong background and interest in statistical computing. <br />The starting date is Fall 2015. <br />For more information about research in the Morota lab at the UNL, visit: http://www.morotalab.org</p>

<p>A letter of interest in the position, C.V., and contact information for <br />three references should be emailed to Gota Morota at . <br />Review of applications will begin immediately, and continue until the <br />positions are filled. Informal inquiries are also welcome.</p>

<p>Also, please see: http://animalscience.unl.edu/anscprospectivegraduatestudents</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14905/internship-in-computational-biology</guid>
  <pubDate>Thu, 04 Sep 2014 04:19:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Internship in Computational Biology]]></title>
  <description><![CDATA[
<p>We are looking for a motivated and autonomous intern to study gene expression in hybrid organisms. The student will work on natural hybrids of two or three different species of fungal endosymbionts of grasses. The pupose of this project is to build software allowing us to identify the genomic origin of expressed genes. To do that, the intern will have to analyze expression data (from RNA-seq) to find SNPs on the sequenced mRNAs allowing to identify from which of the parental genome the expressed gene come from. The data will have to be saved in a database using the standard BioSQL schema.</p>

<p>This job will allow the intern to become more familiar with new biological and bioinformatics tools like next generation sequencing, RNA-Seq data analysis and comparative genomics.</p>

<p>To apply for this position, send the following documents (in PDF format) to Dr Pierre-Yves Dupont (email p.y.dupont@massey.ac.nz):</p>

<p>1. A short cover letter.<br />2. A curriculum vitae, with transcript details.<br />3. The names and contact details of two referees willing to provide a confidential letter of recommendation upon request.</p>

<p>Informal enquiries are welcome. Formal applications are due by Sunday 2nd December 2012.<br />Requirements: </p>

<p>This position requires a good understanding of genetic problems, a good command of at least one scripting language (Perl, Python...), a basic knowledge of MySQL or any relational database management system. Knowledge in biological programming libraries (BioPython, BioPerl, BioRuby...), Java, C++ or any compiled language is an asset but not required. Undergraduate or Master degree is required.<br />Contact Information: </p>

<p>Dr. Pierre-Yves Dupont<br />Institute of Molecular BioSciences<br />Massey University<br />Private Bag 11 222<br />Palmerston North 4442<br />NEW ZEALAND</p>

<p>http://massey.genomicus.com/<br />p.y.dupont@massey.ac.nz</p>

<p>Information about the Institute of Molecular BioSciences (http://imbs.massey.ac.nz/) and the Computational Biology Research Group (http://massey.genomicus.com/) is available online. For more information about the position, you can contact Dr Pierre-Yves Dupont (email p.y.dupont@massey.ac.nz).</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/14899/post-doc-positions-at-the-institute-of-evolution-university-of-haifa-haifa-israel</guid>
  <pubDate>Thu, 04 Sep 2014 03:59:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Post-Doc Positions at the Institute of Evolution, University of Haifa, Haifa, Israel]]></title>
  <description><![CDATA[
<p>We are looking for independent, motivated, diligent, laborious, dedicated Bioinformaticians as post-doctorate fellows for a project aimed at revealing the mechanisms of cancer-resistance and anti-cancer activity of the hypoxia-tolerant subterranean, blind mole-rat, Spalax along its underground evolutionary adaptations. Our project has captured the interest of the scientific community and we have ample financial support for the studies. Generous fellowships ($30K to $40K according to qualifications and performance) are available, immediately, for Post-Docs experts in bioinformatics with a background of good understanding biological questions. That is that can independently handle raw output data of RNA-seq / miR seq/ Genomic, analyze it and can interpret intelligently the relevant biological background. Outstanding candidates for PhD experienced in Bioinformatics will also be considered. Familiarity with cancer research is an advantage. Experience of writing manuscripts for publication and a publication record in relevant journals are expected. English skills both oral and written are required. American, Western-European or Israeli education is a significant benefit. </p>

<p>Our present objectives is to identify and isolate the substances secreted by Spalax cells, resolve with which components they interact that are active only on cancer cells, in order to unravel the biological mechanisms and pathways that evolved in Spalax cell machinery and ultimately lead to the death of cancer-cells. The study could attest to be a breakthrough in cancer research, using the long lived, hypoxia- and cancer-tolerant Spalax as a significant biological resource for biomedical research that hopefully could open new horizons in treatment and prevention of cancer in humans. </p>

<p>Contact: The applications should be submitted, together with extended CV and bibliography, summary of past accomplishments, and contact information of 3 referees, to Prof of Research Aaron Avivi (aaron@research.haifa.ac.il) AND Dr. Imad Shams (imadshams@gmail.com). (http://bit.ly/1lywShk) aaron@research.haifa.ac.il </p>

<p>More at http://evolution.haifa.ac.il/index.php/29-people/personal-websites/77-personal-site-avivi</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13338/protein-function-annotation-and-machine-learning-upmc-paris-france</guid>
  <pubDate>Sat, 02 Aug 2014 01:22:52 -0500</pubDate>
  <link></link>
  <title><![CDATA[Protein function annotation and machine learning - UPMC - Paris, France]]></title>
  <description><![CDATA[
<p>Protein function annotation and machine learning - UPMC - Paris, France</p>

<p>Job Description: We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of paris.</p>

<p>Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.</p>

<p>Title: A novel integrative platform for large scale protein annotation that exploits a multitude of diversified probabilistic models in several protein signature databases.</p>

<p>We propose a novel integrated approach for large scale protein annotation that will exploit an unprecedented amount of genomic data as well as sophisticated machine learning techniques and combinatorial optimization approaches taking advantages of High Performance Computing (HPC) environments. The idea is to uncover as much as possible the evolutionary processes of protein sequences that took place throughout the whole tree of life and that affected the evolution of a protein family. We have already demonstrated in a previous work that the problem of functional annotation is inherent to the ability of uncovering such paths. Now, we shall extend this approach to large scale genome annotation by considering 11 different protein databases, constituted by about 10^9 protein sequences, and by producing a large pool of diversified probabilistic models coding for about 10^7 evolutionary protein pathways. Such models will be used to search for specific domains in genomes to be annotated. Our previous methodology needs to be fundamentally improved to deal with this large amount of biological data. In this project, we shall work on the algorithms to reduce the space of models and the search complexity, and we shall implement some important algorithmic changes towards the realization of a powerful integrated annotation tool.</p>

<p>Where: This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.</p>

<p>Start date: September 1st, 2014<br />Contact Person: Alessandra Carbone<br />Contact: alessandra.carbone@lip6.fr</p>
]]></description>
</item>

</channel>
</rss>