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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36603?offset=170</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/44226/rotifers-lab</guid>
  <pubDate>Wed, 08 Mar 2023 23:23:14 -0600</pubDate>
  <link></link>
  <title><![CDATA[Rotifers Lab]]></title>
  <description><![CDATA[
<p>For scientists in the MBL’s Gribble Lab, the rotifer (Brachionus manjavacas) is used as a model organism to study evolution, stress responses, the biology of aging, and maternal effects. Rotifers are small, easy to grow in the lab, have a short lifespan, and share many of their genes with humans. That makes them ideal specimens in which to address questions relevant to human health as well as understand basic biological and evolutionary processes. Brachionus rotifers produces eggs that can be completely dried and frozen for decades, then hatch within a day when exposed to water and light.</p>

<p>https://www.mbl.edu/research/research-organisms/rotifer<br />https://gribblebiolab.org/</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/4959/evolution-and-cancer</guid>
	<pubDate>Fri, 27 Sep 2013 11:28:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/4959/evolution-and-cancer</link>
	<title><![CDATA[Evolution and Cancer]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/j3uKOcNwYBw" frameborder="0" allowfullscreen></iframe>Air date:  Wednesday, January 04, 2012, 3:00:00 PM
Time displayed is Eastern Time, Washington DC Local  
 
Category:  Wednesday Afternoon Lectures  
Description:  There is a broad consensus that cancer is the result of somatic cells having serially gained, by a series of mutations, the ability to grow independently, to recruit resources from the circulation and the stroma, to invade local tissues, and to found anatomically distant metastases, ultimately killing the host. From the point of view of the cancer-causing somatic cell population, this is evolution driven by mutation and selection. Genomics has resulted in a parallel consensus that the central functions of all eukaryotes are highly conserved, not only at the level of individual protein functions, but also complex biological pathways and systems. These ideas motivated a comparison between results of molecular genetic studies of experimental evolution in yeast and the molecular genetic phenomena associated with tumorigenesis and tumor progression. We find some very striking similarities, including recurring genomic rearrangements, alterations of the regulation of specific growth-promoting genes, population-genetic features that affect the fitness trajectories of growth rate variants in evolving populations, and physiological and metabolic similarities derived from the conservation of the basic plan of growth and cell multiplication among all eukaryotes. It is hoped that some of the insights from yeast will aid the interpretation of sequence changes found in tumors, especially in the urgent necessity to distinguish 'driver' from 'passenger' mutations." 

David Botstein's fundamental contributions to modern genetics include the development of genetic methods for understanding biological functions and the discovery of the functions of many yeast and bacterial genes. In 1980, Botstein and three colleagues proposed a method for mapping human genes that laid the groundwork for the Human Genome Project. The basic principle of the mapping scheme was to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms when hybridized to restriction digests, or specific fragments, of an individual's DNA. The method was used in subsequent years to identify several human disease genes, such as Huntington's and BRCA1. Variations of this method enabled the sequencing phase of the Human Genome Project. 

In the 1990s Botstein, having moved to Stanford University School of Medicine, collaborated with Patrick O. Brown of Stanford in exploiting DNA microarrays to study genome-wide gene expression patterns in yeast and in human cancers. This required developing a new statistical method and graphical interface, widely used today to interpret genomic data. Botstein also has helped to create, with Michael Ashburner and Gerald Rubin, a bioinformatics initiative to unify the representation of gene and gene product attributes across all species, called Gene Ontology. He graduated from Harvard College and earned his doctorate from the University of Michigan. He worked at Massachusetts Institute of Technology from 1967 to 1988; served as vice president for science at Genentech from 1988 to 1990; chaired the Department of Genetics at the Stanford University School of Medicine from 1990 to 2003; and joined the Princeton University faculty in 2003. He has sat on numerous editorial boards and was the founding editor of Molecular Biology of the Cell. Among recent major awards, Bostein won the Peter Gruber Foundation Prize in Genetics in 2003, the Apple Science Innovator Award in 2008, and the Albany Medical Center Prize in 2010. 

The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. 

For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series  
Author:  Dr. David Botstein, Princeton University  
Runtime:  00:59:58  

Permanent link:  http://videocast.nih.gov/launch.asp?17046]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44518/virus-bioinformatics-tools</guid>
	<pubDate>Wed, 24 Apr 2024 06:19:55 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44518/virus-bioinformatics-tools</link>
	<title><![CDATA[Virus Bioinformatics Tools]]></title>
	<description><![CDATA[<p><span>Bioinformatics tools play a crucial role in studying viruses, enabling researchers to analyze their genetic makeup, structure, function, and evolution. Here are some commonly used bioinformatics tools for virus research</span></p>
<p>https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947</p><p>Address of the bookmark: <a href="https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947" rel="nofollow">https://evirusbioinfc.notion.site/18e21bc49827484b8a2f84463cb40b8d?v=92e7eb6703be4720abf17a901bc9a947</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/5253/pre-or-postdoctoral-research-fellowship-in-structural-bioinformatics-in-padova</guid>
  <pubDate>Wed, 02 Oct 2013 15:12:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Pre- or postdoctoral research fellowship in Structural Bioinformatics in Padova]]></title>
  <description><![CDATA[
<p>University of Padova (URL: http://protein.bio.unipd.it/)</p>

<p>A research fellowship is available at the BioComputing Laboratory, University of Padova (URL: http://protein.bio.unipd.it/). A highly motivated and creative candidate is sought to work on structural bioinformatics. Specifically, the project entails the development of novel methods, tools and databases for the analysis of protein structures. The BioComputing Laboratory is a group of a dozen people working on several aspects of prediction of protein structure &amp; function employing techniques at the intersection between biology, medicine, chemistry, physics &amp; computer science. Our aim is to integrate the development of novel methods and their application to biologically relevant problems. We are looking for candidates with a solid Bioinformatics background, programming experience (Python, Perl, C++ and/or Java) and good knowledge of molecular biology (protein structure/function, signalling pathways). Candidates should have a degree with top marks, optionally hold a PhD, and be highly motivated to work on interdisciplinary research. Good knowledge of English, an open-minded spirit, being collaborative and creative are crucial. The fellowship, which should start in late 2013, is initially for one year. It will be commensurate to experience, can be extended depending on performance and may lead to a PhD degree. The successful candidate will be located at the BioComputing Laboratory, University of Padova. Travel support for conferences and/or research visits abroad may be provided. To apply, please send your CV, a brief description of your research background and the names of two (or more) references to Prof. Silvio Tosatto (Email: silvio.tosatto@unipd.it). </p>

<p>Contact Person (Referent): Silvio Tosatto<br />Ref. E-Mail: silvio.tosatto@unipd.it<br />Tel: +39 049 827 6269<br />Fax: +39 049 827 6260<br />Group Web Page: http://protein.bio.unipd.it/</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/44727/postdoctoral-scholar-in-bacterial-evolution-at-pathogen-and-microbiome-institute-at-northern-arizona-university</guid>
  <pubDate>Fri, 13 Dec 2024 12:49:16 -0600</pubDate>
  <link></link>
  <title><![CDATA[Postdoctoral Scholar in Bacterial Evolution at Pathogen and Microbiome Institute at Northern Arizona University]]></title>
  <description><![CDATA[
<p>We are pleased to announce a Postdoctoral Scholar position to study<br />bacterial evolution at the Pathogen and Microbiome Institute at<br />Northern Arizona University with Professor Paul Keim. The scholar<br />will have the opportunity also work with Professor Sam Sheppard at<br />The University of Oxford on joint projects. See our recent paper<br />on interspecific gene flow in Campylobacter. (DOI:<br />https://doi.org/10.1128/mbio.00581-24)</p>

<p>The job description: "This research position focuses on the science<br />of bacterial evolution. It will consist of researching theoretical<br />principles, but could include translational applications. Phylogenomic<br />and bioinformatic analysis of bacterial populations in nature or<br />in laboratory experiments will be a key component of the work. Prior<br />experience is an asset though training will be possible at PMI.<br />Likewise, laboratory microbiological, molecular, and biochemical<br />skills are an asset though not essential. Communication and critical<br />thinking skills are essential for performing the work and for<br />communicating to the local and international scientific communities.<br />Participating in team or independent grant writing to obtain research<br />funding will be required. Student mentoring is a part of the NAU<br />mission and is a partial expectation."</p>

<p>https://hr.peoplesoft.nau.edu/psp/ph92prta/EMPLOYEE/HRMS/c/HRS_HRAM.HRS_APP_SCHJOB.GBL?Page=HRS_APP_JBPST&amp;Action=U&amp;FOCUS=Applicant&amp;SiteId=1&amp;JobOpeningId=608024&amp;PostingSeq=1</p>

<p>Northern Arizona University is located in Flagstaff, Arizona, a<br />beautiful mountain town with a surprisingly vibrant restaurant<br />scene. Located a little over an hour from the Grand Canyon and ~45<br />min from Sedona, Flagstaff is a hiker's paradise. In fact, the city<br />of Flagstaff operates more than 50 miles of unpaved trails and there<br />are, on average, 266 sunny days per year with which to enjoy them.<br />At 7000 ft in elevation, Flagstaff experiences all four seasons,<br />but thesummers are mild and, in the winter, you can be on the ski<br />slopes within 30 min! https://www.flagstaffarizona.org/</p>

<p>As mentioned, joint projects with Professor Sheppard at Oxford<br />University are possible, including travel to his laboratory in the<br />United Kingdom. https://www.biology.ox.ac.uk/people/samuel-sheppard</p>

<p>Contact Information:<br />Paul.Keim@nau.edu</p>

<p>Paul S. Keim, Ph.D.<br />Regents Professor, &amp;<br />Cowden Endowed Chair of Microbiology<br />Northern Arizona University<br />Flagstaff, AZ 86011-4073</p>

<p>Paul S Keim</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7217/contract-faculty-bioinformatics-at-maulana-azad-national-institute-of-technology</guid>
  <pubDate>Thu, 12 Dec 2013 20:46:52 -0600</pubDate>
  <link></link>
  <title><![CDATA[Contract Faculty-Bioinformatics at Maulana Azad National Institute of Technology]]></title>
  <description><![CDATA[
<p>Contract Faculty-Bioinformatics at Maulana Azad National Institute of Technology</p>

<p>Job Description:F.No.11/10(1)/929 Qualifications: Candidates should have Ph.D. degree. If Ph.D. candidates are not available at least Post Graduate degree with GATE/NET qualification is a must. Walk-in-Interview on 19.12.2013 at 2.30 P.M. to 5.30 P.M .. at Maulana Azad National Institute of Technology: Bhopal For more details,please visit website:http://www.manit.ac.in/manitbhopal/Year2013/Recruitment/Contract_faculty/contract%20faculty%202013-2014.pdf</p>

<p>For more @ http://www.manit.ac.in/manitbhopal/Year2013/Recruitment/Contract_faculty/contract%20faculty%202013-2014.pdf</p>

<p>Web address @ :http://www.manit.ac.in</p>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/44700/professorsenior-lecturer-of-comparative-genomics-university-of-glasgow</guid>
  <pubDate>Fri, 06 Dec 2024 05:16:09 -0600</pubDate>
  <link></link>
  <title><![CDATA[Professor/Senior Lecturer of Comparative Genomics @ University of Glasgow]]></title>
  <description><![CDATA[
<p>University of Glasgow<br />College of Medical, Veterinary and Life Sciences<br />School of Biodiversity, One Health and Veterinary Medicine</p>

<p>Professor/Senior Lecturer of Comparative Genomics<br />Vacancy Ref: 153610<br />Salary: Professor, Grade 10 will be within the Professorial range and<br />subject to negotiation<br />Senior Lecturer, Grade 9, 57,696 - 64,914 per annum</p>

<p>The School of Biodiversity, One Health and Veterinary Medicine has an<br />exciting opportunity to appoint a Professor/Senior Lecturer in Comparative<br />Genomics. You will make a substantial and positive contribution to the<br />strategic direction of the School/College through leading and contributing<br />to research of international standard, high quality teaching at both<br />undergraduate and postgraduate level, securing research funding, and<br />providing academic leadership and management within the School/College.</p>

<p>Applications are invited from candidates of international standing with<br />an appropriate record of academic achievement in comparative genomics<br />and associated omics technologies. We are looking for a candidate who<br />will complement our existing strengths in clinical veterinary medicine,<br />evolutionary biology, and animal physiology, with a demonstrable interest<br />in using domestic mammals among their study systems. We are particularly<br />interested in applications from candidates with a track record of<br />studying health related traits and their underlying genomic basis in<br />companion animals. Traits of specific interest include those related<br />to metabolism, ageing, and disease (e.g. cancer, autoimmune diseases,<br />neuromuscular disorders).</p>

<p>The School of Biodiversity, One Health and Veterinary Medicine is home to<br />researchers studying organismal biology and animal health across a diverse<br />range of systems, approaches and disciplines with existing strengths<br />in infectious disease, physiology, ageing, veterinary epidemiology, and<br />evolution among others. You will be based on the University of Glasgow's<br />Garscube campus, where the majority of veterinary teaching and research<br />infrastructure is located. This includes the Small Animal Hospital (a<br />recent 15M investment) and our Veterinary Diagnostic Services, offering<br />excellent opportunities for collaborative research at the clinical and<br />translational interface, especially with respect to companion animals.</p>

<p>We welcome applications from candidates with a Scottish Credit and<br />Qualification Framework level 12 (PhD) in animal biology, genomics and<br />health or related discipline with an extensive and established reputation<br />in research and significant teaching experience within the subject area.</p>

<p>This post is full time and open ended.</p>

<p>Visit our website for further information on The University of<br />Glasgow's, School of Biodiversity, One Health &amp; Veterinary Medicine,<br />https://www.gla.ac.uk/schools/bohvm/</p>

<p>Informal Enquiries should be directed to Professor Roman Biek,<br />Roman.Biek@glasgow.ac.uk</p>

<p>Apply online at:<br />https://my.corehr.com/pls/uogrecruit/erq_jobspec_version_4.jobspec?p_id=153610</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/5623/yau-group</guid>
  <pubDate>Tue, 15 Oct 2013 13:05:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Yau Group]]></title>
  <description><![CDATA[
<p>Yau Group are a new research group based at the Wellcome Trust Centre for Human Genetics and the Department of Statistics at the University of Oxford.</p>

<p>Yau Group develops statistical and computational methods for the analysis of genomic datasets with a particular interest in cancer sequencing applications and the use of Bayesian Statistics.</p>

<p>Yau Group are currently have projects in somatic mutation analysis of heterogeneous cancers, data fusion or integration techniques and single cell genomics.</p>

<p>More @ http://www.well.ox.ac.uk/~cyau/index.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44707/rna-seq-analysis-a-guide-for-bioinformaticians</guid>
	<pubDate>Sat, 07 Dec 2024 22:22:24 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44707/rna-seq-analysis-a-guide-for-bioinformaticians</link>
	<title><![CDATA[RNA-Seq Analysis: A Guide for Bioinformaticians]]></title>
	<description><![CDATA[<p>RNA sequencing (RNA-Seq) has revolutionized transcriptomics, offering unprecedented insights into gene expression, splicing, and transcript diversity. For bioinformaticians, RNA-Seq analysis is a gateway to exploring the complexity of RNA biology and its implications in health and disease. This blog post provides an overview of RNA-Seq analysis, key computational steps, and tools for bioinformaticians eager to delve into this powerful technique.</p><h3>What is RNA-Seq?</h3><p>RNA-Seq is a next-generation sequencing (NGS) technology used to study the transcriptome&mdash;the complete set of RNA molecules in a cell. It quantifies gene expression, detects novel transcripts, and captures alternative splicing events with high sensitivity and resolution.</p><h3>Workflow for RNA-Seq Analysis</h3><p>RNA-Seq analysis involves several stages, each requiring computational tools and expertise.</p><h4>1. <strong>Experimental Design and Data Acquisition</strong></h4><p>Before diving into analysis, bioinformaticians should consider:</p><ul>
<li><strong>Biological Replicates</strong>: Ensure statistical power to detect meaningful differences.</li>
<li><strong>Sequencing Depth</strong>: Align sequencing depth to study objectives (e.g., higher depth for low-abundance transcripts).</li>
<li><strong>Paired-End vs. Single-End</strong>: Paired-end sequencing provides more detailed information on transcript structure.</li>
</ul><p>Once sequencing is complete, raw data is provided in FASTQ format, containing sequence reads and quality scores.</p><h4>2. <strong>Quality Control and Preprocessing</strong></h4><p>Quality control (QC) ensures data integrity. Tools such as <strong>FastQC</strong> evaluate metrics like base quality, GC content, and adapter contamination.</p><p><strong>Preprocessing Steps</strong>:</p><ul>
<li><strong>Trimming</strong>: Tools like <strong>Trimmomatic</strong> or <strong>Cutadapt</strong> remove low-quality bases and adapter sequences.</li>
<li><strong>Filtering</strong>: Discard reads below a certain quality threshold or length.</li>
</ul><h4>3. <strong>Read Alignment</strong></h4><p>Reads are mapped to a reference genome or transcriptome to determine their origin. Alignment tools include:</p><ul>
<li><strong>HISAT2</strong>: Handles large genomes efficiently and supports spliced alignments.</li>
<li><strong>STAR</strong>: High-speed aligner optimized for RNA-Seq.</li>
<li><strong>Bowtie2</strong>: Suitable for short-read alignment.</li>
</ul><p><strong>Output</strong>: A SAM/BAM file containing aligned reads.</p><h4>4. <strong>Transcript Assembly and Quantification</strong></h4><p>This step involves identifying transcripts and quantifying their expression levels. Tools used include:</p><ul>
<li><strong>StringTie</strong>: Assembles and quantifies transcripts from aligned reads.</li>
<li><strong>Salmon/Kallisto</strong>: Perform pseudo-alignment for rapid and accurate quantification.</li>
</ul><p>Expression levels are typically measured as TPM (transcripts per million) or FPKM (fragments per kilobase of transcript per million mapped reads).</p><h4>5. <strong>Differential Expression Analysis</strong></h4><p>To identify genes with altered expression between conditions, bioinformaticians use tools such as:</p><ul>
<li><strong>DESeq2</strong>: Accounts for data normalization and variability.</li>
<li><strong>edgeR</strong>: Handles overdispersed count data efficiently.</li>
<li><strong>Limma-voom</strong>: Combines linear modeling with RNA-Seq count data.</li>
</ul><p>The output includes a list of differentially expressed genes (DEGs) with statistical significance and fold-change values.</p><h4>6. <strong>Functional Annotation and Pathway Analysis</strong></h4><p>Understanding the biological significance of DEGs involves:</p><ul>
<li><strong>Gene Ontology (GO) Analysis</strong>: Tools like <strong>DAVID</strong> or <strong>clusterProfiler</strong> categorize genes based on their biological functions.</li>
<li><strong>Pathway Enrichment Analysis</strong>: Identifies pathways enriched in DEGs using tools like <strong>KEGG</strong>, <strong>Reactome</strong>, or <strong>GSEA</strong>.</li>
</ul><h4>7. <strong>Visualization</strong></h4><p>Visualizing results enhances interpretability. Common visualizations include:</p><ul>
<li><strong>Heatmaps</strong>: Show expression patterns across samples (e.g., <strong>pheatmap</strong>).</li>
<li><strong>Volcano Plots</strong>: Highlight significant DEGs (e.g., <strong>ggplot2</strong>).</li>
<li><strong>PCA/UMAP</strong>: Assess sample clustering and variability (e.g., <strong>Seurat</strong>).</li>
</ul><h3>Challenges in RNA-Seq Analysis</h3><ol>
<li><strong>Batch Effects</strong>: Technical variability can confound biological signals. Combat this with normalization techniques or batch-correction tools like <strong>ComBat</strong>.</li>
<li><strong>Low-Quality Samples</strong>: Poor-quality RNA impacts downstream analyses.</li>
<li><strong>Computational Complexity</strong>: RNA-Seq generates massive datasets, requiring robust computing resources and optimized pipelines.</li>
</ol><h3>Key Tools and Resources</h3><ul>
<li><strong>Bioconductor</strong>: A treasure trove of R packages for RNA-Seq analysis.</li>
<li><strong>Galaxy</strong>: A web-based platform for running RNA-Seq workflows.</li>
<li><strong>Nextflow/Snakemake</strong>: Workflow management tools to streamline analyses.</li>
</ul><h3>Applications of RNA-Seq</h3><p>RNA-Seq is used in diverse research areas, including:</p><ul>
<li><strong>Cancer Transcriptomics</strong>: Identifying tumor-specific expression profiles.</li>
<li><strong>Developmental Biology</strong>: Studying dynamic transcriptome changes.</li>
<li><strong>Drug Discovery</strong>: Screening genes modulated by therapeutic compounds.</li>
</ul><h3>Conclusion</h3><p>RNA-Seq analysis is a cornerstone of modern transcriptomics, offering bioinformaticians a versatile toolkit for unraveling gene expression and regulation. Mastering RNA-Seq workflows and tools empowers researchers to transform raw sequencing data into biological discoveries.</p><p>Whether you&rsquo;re investigating disease mechanisms, exploring cellular pathways, or developing new therapeutics, RNA-Seq is a powerful ally in your bioinformatics arsenal.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/7218/associate-professor-centre-for-bioinformatics-at-maharshi-dayanand-university-rohtak</guid>
  <pubDate>Thu, 12 Dec 2013 20:49:59 -0600</pubDate>
  <link></link>
  <title><![CDATA[Associate Professor - Centre for Bioinformatics at Maharshi Dayanand University, Rohtak]]></title>
  <description><![CDATA[
<p>ADVERTISEMENT No. PR-54/2013</p>

<p>No. of Posts and Specialization: 1(UR)</p>

<p>Educational Qualification:</p>

<p>(i) Good academic record with a Ph.D. Degree in the concerned /allied /relevant disciplines.</p>

<p>(ii) The Ph.D. Degree shall be a mandatory qualification for all candidates to be appointed as Associate Professor through direct recruitment.</p>

<p>(iii) A Master‟s Degree with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed).</p>

<p>(iv) A minimum of eight years of experience of teaching and /or research in an academic /research position equivalent to that of Assistant Professor in a University, College or Accredited Research Institution/Industry excluding the period of Ph.D research with evidence of published work and a minimum of 5 publications as books and /or research papers in refereed journals only/policy papers.</p>

<p>(v) Contribution to educations innovation, design of new curricula and courses and technology-mediated teaching learning process with evidence of having guided doctoral candidates and research students.</p>

<p>(vi) A minimum score as stipulated in the Academic Performance Indicator (API) based performance Based Appraisal System (PBAS), set out in this notification in as mentioned in the advertisement.</p>

<p>Send your application to the A.R (Estt.Teaching), M.D.University, Rohtak on or before December 23, 2013.</p>

<p>For more details: http://www.mdurohtak.ac.in/pdf/Notices_Pdf/new_notice/Teaching%20Vacancy%20%28ADVT.%20No.%20PR-54%20of%202013%29.pdf</p>

<p>Last Apply Date: 23 Dec 2013</p>
]]></description>
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