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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/33629?offset=1130</link>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10380/ra-at-alagappa-university</guid>
  <pubDate>Sun, 04 May 2014 23:33:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA at ALAGAPPA UNIVERSITY]]></title>
  <description><![CDATA[
<p>DEPARTMENT OF BIOTECHNOLOGY<br />(UGC SAP and DST-FIST &amp; PURSE Sponsored Department)<br />ALAGAPPA UNIVERSITY<br />(A State University Accredited by NAAC with „A‟ Grade)<br />Karaikudi - 630 004, India</p>

<p>WALK IN INTERVIEW</p>

<p>A walk-in Interview for the following position tenable at the Bioinformatics Infrastructure Facility (BIF), Department of Biotechnology, Alagappa University will be held at the Department of Biotechnology, Alagappa University, Karaikudi 630 003 on 15.05.2014 (Thursday) at 01:00 PM. This national facility is funded by the Department of Biotechnology, Ministry of Science and Technology, Government of India, New Delhi. The main objectives of the Centre involve teaching and research activities in bioinformatics/biotechnology.</p>

<p>RA (One Post):</p>

<p>Salary : Rs. 11000 p.m. plus admissible HRA</p>

<p>Qualification: M.Sc., in Bioinformatics/Biotechnology/Biophysics/Biochemistry/ Life Sciences</p>

<p>Interested candidates are encouraged to send their Curriculum Vitae by email to “sk_pandian@rediffmail.com” in advance. On the day of interview, the candidates must produce original certificates in proof of their educational qualification and experience and a recommendation letter from the Head of the Department/Institution where last studied/worked. Candidates who have already passed the required Degree alone are eligible to appear for interview. No TA&amp;DA will be given for attending the interview.</p>

<p>Advertisement: http://www.alagappabiotech.org/Walk%20in%20interview.pdf</p>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44734/data-visualization-in-bioinformatics-useful-and-eye-catching-plots-for-data-analysis</guid>
	<pubDate>Sat, 14 Dec 2024 12:41:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44734/data-visualization-in-bioinformatics-useful-and-eye-catching-plots-for-data-analysis</link>
	<title><![CDATA[Data Visualization in Bioinformatics: Useful and Eye-Catching Plots for Data Analysis]]></title>
	<description><![CDATA[<p>Data visualization is a cornerstone of bioinformatics, enabling researchers to interpret complex datasets effectively. With a plethora of data types&mdash;genomic sequences, expression profiles, protein interactions, and more&mdash;the right visualizations can make or break an analysis. This blog highlights some of the most useful and visually compelling plots for bioinformatics data analysis, along with tools to create them.</p><h4><strong>1. Heatmaps: Exploring Patterns in High-Dimensional Data</strong></h4><p>Heatmaps are a go-to visualization for representing high-dimensional datasets, such as gene expression or metabolomics data. They use color gradients to display data intensity, making patterns and clusters easily detectable.</p><ul>
<li>
<p><strong>Applications</strong>: Gene expression analysis, pathway enrichment, methylation studies.</p>
</li>
<li>
<p><strong>Tools</strong>: Seaborn (Python), ComplexHeatmap (R), Morpheus (web-based).</p>
</li>
</ul><p><strong>Tip</strong>: Add dendrograms to visualize clustering of rows and columns for hierarchical relationships.</p><h4><strong>2. Volcano Plots: Highlighting Differential Features</strong></h4><p>Volcano plots are indispensable for identifying significantly differentially expressed genes or proteins. They plot the log2 fold change against &ndash;log10(p-value), making it easy to spot statistically significant changes.</p><ul>
<li>
<p><strong>Applications</strong>: RNA-seq, proteomics, and metabolomics.</p>
</li>
<li>
<p><strong>Tools</strong>: ggplot2 (R), EnhancedVolcano (R), Plotly (Python).</p>
</li>
</ul><p><strong>Tip</strong>: Use color to highlight significant features and label key genes or proteins.</p><h4><strong>3. PCA Plots: Reducing Complexity with Principal Component Analysis</strong></h4><p>Principal Component Analysis (PCA) plots are used to reduce dimensionality and uncover trends or clusters in data. They provide insights into sample variability and grouping.</p><ul>
<li>
<p><strong>Applications</strong>: Transcriptomics, metabolomics, microbiome studies.</p>
</li>
<li>
<p><strong>Tools</strong>: scikit-learn + Matplotlib (Python), prcomp (R), ClustVis (web-based).</p>
</li>
</ul><p><strong>Tip</strong>: Annotate clusters with metadata to enhance interpretability.</p><h4><strong>4. Manhattan Plots: Genome-Wide Association Studies</strong></h4><p>Manhattan plots visualize p-values across the genome, making it easy to identify significant associations in genome-wide studies. They resemble city skylines, with the highest peaks indicating loci of interest.</p><ul>
<li>
<p><strong>Applications</strong>: GWAS, QTL mapping.</p>
</li>
<li>
<p><strong>Tools</strong>: qqman (R), Matplotlib (Python).</p>
</li>
</ul><p><strong>Tip</strong>: Use alternating colors for chromosomes and highlight significant SNPs for clarity.</p><h4><strong>5. Circular Plots (Circos): Visualizing Genomic Relationships</strong></h4><p>Circular plots are ideal for visualizing relationships across the genome, such as structural variations, gene duplications, or synteny.</p><ul>
<li>
<p><strong>Applications</strong>: Comparative genomics, structural variation studies.</p>
</li>
<li>
<p><strong>Tools</strong>: Circos (standalone), Rcircos (R), pyCircos (Python).</p>
</li>
</ul><p><strong>Tip</strong>: Keep the plot clean and avoid overcrowding to maintain readability.</p><h4><strong>6. Sankey Diagrams: Tracking Data Flows</strong></h4><p>Sankey diagrams visualize flows or relationships between categories, often used to track changes in gene expression or pathway enrichment across conditions.</p><ul>
<li>
<p><strong>Applications</strong>: Pathway analysis, gene set enrichment analysis.</p>
</li>
<li>
<p><strong>Tools</strong>: Plotly (Python), networkD3 (R).</p>
</li>
</ul><p><strong>Tip</strong>: Use gradients or distinct colors to highlight key transitions.</p><h4><strong>7. Network Graphs: Mapping Interactions</strong></h4><p>Network graphs represent relationships between entities, such as protein-protein interactions or gene regulatory networks. Nodes represent entities, and edges represent relationships.</p><ul>
<li>
<p><strong>Applications</strong>: Systems biology, interactomics.</p>
</li>
<li>
<p><strong>Tools</strong>: Cytoscape (standalone), igraph (R), NetworkX (Python).</p>
</li>
</ul><p><strong>Tip</strong>: Use edge thickness or node size to represent interaction strength or centrality.</p><h4><strong>8. Violin Plots: Visualizing Data Distribution</strong></h4><p>Violin plots combine a boxplot with a density plot, showing the distribution and variability of data.</p><ul>
<li>
<p><strong>Applications</strong>: Single-cell RNA-seq, quantitative trait analysis.</p>
</li>
<li>
<p><strong>Tools</strong>: Seaborn (Python), ggplot2 (R).</p>
</li>
</ul><p><strong>Tip</strong>: Split violins by groups for side-by-side comparisons.</p><h4><strong>9. Time-Series Plots: Monitoring Changes Over Time</strong></h4><p>Time-series plots display changes in variables across time points, useful for tracking gene expression dynamics or metabolic fluxes.</p><ul>
<li>
<p><strong>Applications</strong>: Time-course experiments, cell cycle studies.</p>
</li>
<li>
<p><strong>Tools</strong>: Matplotlib (Python), ggplot2 (R).</p>
</li>
</ul><p><strong>Tip</strong>: Smooth the data to highlight trends while avoiding overfitting.</p><h4><strong>10. Genome Tracks: Visualizing Genomic Features</strong></h4><p>Genome tracks display multiple layers of genomic data, such as gene annotations, sequencing coverage, and epigenetic marks.</p><ul>
<li>
<p><strong>Applications</strong>: ChIP-seq, ATAC-seq, whole-genome sequencing.</p>
</li>
<li>
<p><strong>Tools</strong>: IGV (standalone), pyGenomeTracks (Python).</p>
</li>
</ul><p><strong>Tip</strong>: Stack related tracks for direct comparisons.</p><h4><strong>11. UpSet Plots: Visualizing Set Intersections</strong></h4><p>UpSet plots are a powerful alternative to Venn diagrams for visualizing intersections between multiple datasets.</p><ul>
<li>
<p><strong>Applications</strong>: Overlap analysis for gene sets, pathways, or variants.</p>
</li>
<li>
<p><strong>Tools</strong>: UpSetR (R), ComplexUpset (Python).</p>
</li>
</ul><p><strong>Tip</strong>: Use bar plots to represent the size of each intersection for added clarity.</p><h4><strong>12. Ridge Plots: Comparing Distributions</strong></h4><p>Ridge plots visualize the distributions of multiple datasets, stacked for easy comparison.</p><ul>
<li>
<p><strong>Applications</strong>: Transcriptomics, single-cell RNA-seq.</p>
</li>
<li>
<p><strong>Tools</strong>: ggridges (R), Matplotlib (Python).</p>
</li>
</ul><p><strong>Tip</strong>: Use transparency and consistent scaling for better readability.</p><h4><strong>13. Chord Diagrams: Visualizing Connections Between Groups</strong></h4><p>Chord diagrams illustrate relationships between categories, such as shared genes between pathways or overlaps in regulatory elements.</p><ul>
<li>
<p><strong>Applications</strong>: Pathway overlap, synteny, co-expression networks.</p>
</li>
<li>
<p><strong>Tools</strong>: Circlize (R), Holoviews (Python).</p>
</li>
</ul><p><strong>Tip</strong>: Use distinct colors for each group to emphasize relationships.</p><h4><strong>14. Treemaps: Hierarchical Data Representation</strong></h4><p>Treemaps visualize hierarchical data as nested rectangles, with area proportional to data size.</p><ul>
<li>
<p><strong>Applications</strong>: Ontology enrichment, pathway analysis.</p>
</li>
<li>
<p><strong>Tools</strong>: Treemapify (R), Plotly (Python).</p>
</li>
</ul><p><strong>Tip</strong>: Use colors to represent additional variables, like significance or enrichment scores.</p><h4><strong>15. T-SNE/UMAP Plots: Dimensionality Reduction for Clustering</strong></h4><p>T-SNE and UMAP plots are great for visualizing high-dimensional data in two dimensions while preserving local or global structure.</p><ul>
<li>
<p><strong>Applications</strong>: Single-cell transcriptomics, clustering analyses.</p>
</li>
<li>
<p><strong>Tools</strong>: scikit-learn (Python), Seurat (R).</p>
</li>
</ul><p><strong>Tip</strong>: Combine with metadata annotations for better cluster interpretation.</p><h4><strong>Bringing It All Together</strong></h4><p>The choice of visualization can significantly impact the insights gained from bioinformatics data. By selecting plots tailored to your data type and analysis goals, you can effectively communicate your findings and make your research more impactful. Whether you&rsquo;re a seasoned bioinformatician or a beginner, mastering these visualizations will elevate your analyses and presentations.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10459/associate-professor-bio-informatics-at-university-of-allahabad-in-allahabad</guid>
  <pubDate>Wed, 07 May 2014 00:26:53 -0500</pubDate>
  <link></link>
  <title><![CDATA[Associate Professor - Bio-Informatics at University of Allahabad in Allahabad]]></title>
  <description><![CDATA[
<p>No of vacancies: 01</p>

<p>Pay scale: Pay Band of Rs. 37400-67000 with AGP of Rs. 9000.</p>

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

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

<p>iii. 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/policy papers.</p>

<p>iv. Contribution to educational 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>v. A minimum score as stipulated in the Academic Performance Indicator (API) based Performance Based Appraisal System (PBAS), set out in UGC Regulation.</p>

<p>Download application form from website: http://www.allduniv.ac.in/</p>

<p>Send your application to the Registrar, University of Allahabad, Allahabad-211002 (U.P.) on or before 30th April 2014</p>

<p>For more details: http://www.allduniv.ac.in/images/adv/backlog/advt-details.pdf OR http://www.allduniv.ac.in/images/news/extension-notice.pdf</p>

<p>Last Apply Date: 30 May 2014</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/6052/university-of-california-irvine-center-for-complex-biological-systems</guid>
	<pubDate>Mon, 04 Nov 2013 17:10:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/6052/university-of-california-irvine-center-for-complex-biological-systems</link>
	<title><![CDATA[University of California, Irvine - Center for Complex Biological Systems]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/chPJ6OdVl4o" frameborder="0" allowfullscreen></iframe>The University of California Irvine's Center for Complex Biological Systems got its start just as there was a revolution in biology. Systems Biology requires that scientists work across many disciplines including engineering, physics and mathematics. The Center specializes in helping form the kinds of teams that will propel biological research into the future. It is also proud to be able to train students in the new interdisciplinary approach.

http://ccbs.uci.edu]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10664/dna-replication-process-3d-animation</guid>
	<pubDate>Sat, 10 May 2014 04:41:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10664/dna-replication-process-3d-animation</link>
	<title><![CDATA[DNA Replication Process [3D Animation]]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/27TxKoFU2Nw" frameborder="0" allowfullscreen></iframe>See an organised list of all the animations: http://doctorprodigious.wordpress.com/hd-animations/]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/38548/assistant-professor-at-sher-e-kashmir-university-of-agricultural-sciences-technology-of-jammu</guid>
  <pubDate>Sat, 29 Dec 2018 13:05:37 -0600</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor at Sher-e- Kashmir  University of Agricultural Sciences &amp; Technology of Jammu]]></title>
  <description><![CDATA[
<p>Sher-e- Kashmir <br />University of Agricultural Sciences &amp; Technology of Jammu <br />School of Biotechnology </p>

<p>Applications are invited from candidates for the temporary positions on contractual basis for academic arrangement in the School of Biotechnology, SKUAST-J: </p>

<p>3 Assistant Professor (Bioinformatics) (01) </p>

<p>Rs. 25000/- per month for Ph.D. and Rs. 20000/- per month for M. Sc. (Fixed) </p>

<p>High second class M.Sc. degree (55 % marks) in Biotechnology/ Bioinformatics </p>

<p>NET in concerned subject/ Ph.D. &amp; Teaching/ research experience in Bioinformatics/ Computational Biology as evident from documents /publications </p>

<p>The application should reach the office of Coordinator, School of Biotechnology, SKUAST-J, Chatha, Jammu-180009 (J&amp;K) along with attested copies of the certificates on or before 10.01.2019 through registered post only. </p>

<p>More Info: http://skuast.org/site/Templates%20HTML/jobs/2018/ap-sbt-21-12-2018.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10748/bioinformatics-phd-at-cuk-kerala</guid>
  <pubDate>Sat, 10 May 2014 20:21:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics PhD at CUK Kerala]]></title>
  <description><![CDATA[
<p>Applications are invited from highly motivated students (UGC-CSIR-JRF) with a background in Genomics/ Biotechnology/ Molecular Microbiology/ Biochemistry and Bioinformatics to pursue research leading to Ph.D. in the following areas;</p>

<p>    1. Cancer Genomics</p>

<p>    2. Microbial Genetics and Metagenomics</p>

<p>    3. Human Infective Diseases</p>

<p>    4. Computational Drug Design</p>

<p>Interested candidates may apply to Dr. Ranjith N. Kumavath, Assistant Professor &amp; Head, Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Padannakad (PO), Nileshwar, Kasaragod-671328,Kerala. Email: RNkumavath@gmail.com</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/36299/faulty-post-at-maharshi-dayanand-university-rohtak</guid>
  <pubDate>Mon, 23 Apr 2018 05:07:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[FAULTY POST AT MAHARSHI DAYANAND UNIVERSITY, ROHTAK]]></title>
  <description><![CDATA[
<p>ADVT. NO. PR-28 of 2018 </p>

<p>Online applications are invited from eligible &amp; interested candidates for the following Teaching/Non-Teaching posts. Applications must be submitted online from 10.4.2018 to 30.4.2018 through the link available on the university website www.mdurohtak.ac.in </p>

<p>Applicants must read the instructions carefully before proceeding to fill the form. The detailed information/instructions/eligibility criteria are available on the university website www.mdurohtak.ac.in </p>

<p>Budgeted: </p>

<p>Teaching posts:- </p>

<p>Botany: Assistant Professor-1(UR); Biochemistry: Associate Professor-1(UR), Assistant Professor-2(UR-1, SC-1); Centre for Biotechnology: Assistant Professor-1(UR); Centre for Bioinformatics: Associate Professor-1(UR), Assistant Professor-1(SC); Chaudhary Ranbir Singh Institute of Social &amp; Economic Change: Assistant Professor-1(UR); Computer Science &amp; Applications: Assistant Professor-4(UR-3,SC-1); Environmental Science: Assistant Professor-1(UR); Food Technology: Assistant Professor:-2(UR-1, SC-1), Genetics: Professor-1(UR); Microbiology: Assistant Professor-1(SC); Pharmaceutical Sciences: Assistant Professor-1{ESM(UR)}; Physics: Assistant Professor-5{UR-1, SC-2, BC(A)-1, ESM(UR)-1}</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10925/a-brief-bioinformatics-tutorial</guid>
	<pubDate>Wed, 21 May 2014 12:50:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10925/a-brief-bioinformatics-tutorial</link>
	<title><![CDATA[A Brief Bioinformatics Tutorial]]></title>
	<description><![CDATA[<p>This is about how to use a computer to find what is known about a gene of interest and also how to get new insights about it.</p>
<p>The tutorial is divided in three main parts:</p>
<ul>
<li>In the <strong>Sequence </strong>part, you will see how to look efficiently for a particular protein sequence, how to blast it against the database of your choice to find homologues, how to perform a multiple alignment of the homologues you've selected and how to edit this alignment.</li>
<li>The <strong>Structure </strong>part is about molecular visualization, homology modeling and structural domain prediction.</li>
<li>In the <strong>Function </strong>part, you will be introduced to you 3 useful servers to investigate the function of a protein. i.e. finding interactors, co-expressed genes, see a phylogenetic profile, easily access papers citing your gene etc ...</li>
</ul>
<p>During all the three parts, we will use the <em>S. cerevisiae </em>VPS36 protein as an example.</p><p>Address of the bookmark: <a href="http://www.mrc-lmb.cam.ac.uk/rlw/text/bioinfo_tuto/introduction.html" rel="nofollow">http://www.mrc-lmb.cam.ac.uk/rlw/text/bioinfo_tuto/introduction.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11035/bioinformatics-jrfsrf-position-at-nii</guid>
  <pubDate>Sun, 25 May 2014 16:54:04 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF/SRF position at NII]]></title>
  <description><![CDATA[
<p>NATIONAL INSTITUTE OF IMMUNOLOGY, NEW DELHI-110067</p>

<p>Applications are invited for the position of Senior Research Fellow for the following time-bound sponsored project as per the details given below:</p>

<p>1. BTIS project on, “Bioinformatics Center-National Infrastructural Facility in the Area of Immunology” funded by DBT</p>

<p>Senior Research Fellow (P) (One Position only)</p>

<p>Dr. Debasisa Mohanty<br />Staff Scientist-VI<br />deb@nii.res.in</p>

<p>Qualifications: M.Sc in Biological Sciences or Biotechnology with at least 04 years of Research experience in Bioinformatics or computational Biology after the master’s degree is essential.</p>

<p>Emoluments: The selected candidates will draw consolidated emoluments as per Institute Rules, depending upon qualifications &amp; experience</p>

<p>Rs. 18,000/- per month consolidated plus 30% HRA if Leading to Ph.D/NET/GATE Qualified otherwise Rs. 14,000/- per month + 30% HRA.</p>

<p>Job description: The candidate should be well versed in programming in PERL/C++/HTML/CGI, web server and portal development, computational analysis of<br />protein structure &amp; function, molecular dynamics simulations and use of high performance computing systems.</p>

<p>GENERAL TERMS AND CONDITIONS:-</p>

<p>1. The candidates selected for the above posts will be on contract for one year or duration of the project whichever is shorter, at a time.<br />2. No hostel/ housing facility will be provided.<br />3. Number of posts may vary and shall be need based. Advertisement is no commitment.<br />4. Applicants may clearly mention the category they belong to i.e. SC/ST/OBC/PH and attach documentary proof of the same.<br />5. No TA/DA will be paid for attending the interview, if called for.<br />6. Apart from sending application in the prescribed format given below, candidates should send complete Curriculum Vitae along with the names of three referees. Curriculum Vitae should contain details of the experimental expertise.</p>

<p>HOW TO APPLY Interested candidates may apply directly, STRICTLY IN THE PRESCRIBED FORMAT GIVEN BELOW, through e-mail, to the Investigator of the project, clearly indicating the name of the project along with their complete C.V., e-mail id, fax numbers, telephone numbers. Only Short listed candidates will be called for interview and they required to submit attested copies of all their certificates and a Demand Draft of Rs 100/- drawn on Canara Bank or Indian Bank payable at Delhi/New Delhi in favour of the Director, NII (SC / ST and PH candidates are exempted subject to submission of documentary proof), at the time of interview.</p>

<p>LAST DATE OF RECEIPT OF APPLICATIONS: 06th June, 2014</p>

<p>Advertisement</p>

<p>www1.nii.res.in/sites/default/files/projectappointment-Dr.Mohanty-6June2014.pdf</p>
]]></description>
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