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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/30364?offset=90</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27971/samtools-primer</guid>
	<pubDate>Thu, 23 Jun 2016 07:18:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27971/samtools-primer</link>
	<title><![CDATA[Samtools Primer !!]]></title>
	<description><![CDATA[<p>SAMtools: Primer / Tutorial by Ethan Cerami, Ph.D.<br><br>keywords: samtools, next-gen, next-generation, sequencing, bowtie, sam, bam, primer, tutorial, how-to, introduction<br>Revisions<br><br>&nbsp;&nbsp;&nbsp; 1.0: May 30, 2013: First public release on biobits.org.<br>&nbsp;&nbsp;&nbsp; 1.1: July 24, 2013: Updated with Disqus Comments / Feedback section.<br>&nbsp;&nbsp;&nbsp; 1.2: December 19, 2014: Multiple updates, including:<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Updated to use samtools 1.1 and bcftools 1.2.<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Updated usage for bcftools.<br><br>About<br><br>SAMtools is a popular open-source tool used in next-generation sequence analysis. This primer provides an introduction to SAMtools, and is geared towards those new to next-generation sequence analysis. The primer is also designed to be self-contained and hands-on, meaning that you only need to install SAMtools, and no other tools, and sample data sets are provided. Terms in bold are also explained in the glossary at the end of the document.</p><p>Address of the bookmark: <a href="http://biobits.org/samtools_primer.html" rel="nofollow">http://biobits.org/samtools_primer.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/28112/ngs-glossary</guid>
	<pubDate>Mon, 27 Jun 2016 08:56:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/28112/ngs-glossary</link>
	<title><![CDATA[NGS Glossary !!]]></title>
	<description><![CDATA[<p><strong>alignment</strong>: the mapping of a raw sequence read to a location within a reference genome. The mapping occurs because the sequences within the raw read match or align to sequences within the reference genome. Alignment information is stored in the <strong>SAM</strong> or <strong>BAM</strong> file formats.</p><p><strong>bcftools</strong>: a set of companion tools, currently bundled with SAMtools, for identifying and filtering genomics variants.</p><p><strong>bowtie</strong>: widely used, open source alignment software for aligning raw sequence reads to a reference genome.</p><p><strong>BAM Format</strong>: binary, compressed format for storing <strong>SAM</strong> data.</p><p><strong>BCF Format</strong>: Binary call format. Binary, compressed format for storing <strong>VCF</strong> data.</p><p><strong>CIGAR String</strong>: Compact Idiosyncratic Gapped Alignment Report. A compact string that (partially) summarizes the alignment of a raw sequence read to the reference genome. Three core abbreviations are used: M for alignment match; I for insertion; and D for Deletion. For example, a CIGAR string of 5M2I63M indicates that the first 5 base pairs of the read align to the reference, followed by 2 base pairs, which are unique to the read, and not in the reference genome, followed by an additional 63 base pairs of alignment.</p><p><strong>FASTA Format</strong>: text format for storing raw sequence data. For example, the FASTA file at: <a href="http://www.ncbi.nlm.nih.gov/nuccore/NC_008253">http://www.ncbi.nlm.nih.gov/nuccore/NC_008253</a> contains entire genome for Escherichia coli 536.</p><p><strong>FASTQ Format</strong>: text format for storing raw sequence data along with quality scores for each base; usually generated by sequencing machines.</p><p><strong>genotype likelihood</strong>: the probability that a specific genotype is present in the sample of interest. Genotype likelihoods are usually expressed as a <strong>Phred-scaled probability</strong>, where P = 10 ^ (-Q/10). For example, if the genotype TT (both alleles are T) at position 1,299,132 in human chromosome 12 (reference G) is 37, this translates to a probability of 10<sup>-37/10</sup> = 0.0001995, meaning that there is very low probability that the reads in your sample support a TT genotype. On the other hand, a genotype of AA at the same position with a score of 0 translates into a probability of 10<sup>-0</sup> = 1, indicating extremely high probability that your sample contains a homozygous mutation of G to A.</p><p><strong>mate-pair</strong>: in paired-end sequencing, both ends of a single DNA or RNA fragment are sequenced, but the intermediate region is not. The two ends which are sequenced form a pair, and are frequently referred to as mate-pairs.</p><p><strong>QNAME</strong>: unique identifier of a raw sequence read (also known as the Query Name). Used in <strong>FASTQ</strong> and <strong>SAM</strong> files.</p><p><strong>paired-end sequencing</strong>: sequencing process where both ends of a single DNA or RNA fragment are sequenced, but the intermediate region is not. Particularly useful for identifying structural rearrangements, including gene fusions.</p><p><strong>Phred-scaled probability</strong>: a scaled value (Q) used to compactly summarize a probability, where P = 10<sup>-Q/10</sup>. For example, a Phred Q score of 10 translates to probability (P) = 10<sup>-10/10</sup> = 0.1. Phred-scaled probabilities are common in next-generation sequencing, and are used to represent multiple types of quality metrics, including quality of base calls, quality of mappings, and probabilities associated with specific genotypes. The name Phred refers to the original Phred base-calling software, which first used and developed the scale.</p><p><strong>Phred quality score</strong>: a score assigned to each base within a sequence, quantifying the probability that the base was called incorrectly. Scores use a <strong>Phred-scaled probability</strong> metric. For example, a Phred Q score of 10 translates to P=10<sup>-10/10</sup> = 0.1, indicating that the base has a 0.1 probability of being incorrect. Higher Phred score correspond to higher accuracy. In the <strong>FASTQ format</strong>, Phred scores are represented as single ASCII letters. For details on translating between Phred scores and ASCII values, refer to <a href="http://www.somewhereville.com/?p=1508">Table 1 of this useful blog post from Damian Gregory Allis</a>.</p><p><strong>read-length</strong>: the number of base pairs that are sequenced in an individual sequence read.</p><p><strong>read-depth</strong>: the number of sequence reads that pile up at the same genomic location. For example, 30X read-depth coverage indicates that the genomic location is covered by 30 independent sequencing reads. Increased read-depth translates into higher confidence for calling genomic variants.</p><p><strong>RNAME</strong>: reference genome identifier (also known as the Reference Name). Within a SAM formatted file, the RNAME identifies the reference genome where the raw read aligns.</p><p><strong>SAM Flag</strong>: a single integer value (e.g. 16), which encodes multiple elements of meta-data regarding a read and its alignment. Elements include: whether the read is one part of a paired-end read, whether the read aligns to the genome, and whether the read aligns to the forward or reverse strand of the genome. A <a href="http://picard.sourceforge.net/explain-flags.html">useful online utility</a> decodes a single SAM flag value into plain English.</p><p><strong>SAM Format</strong>: Text file format for storing sequence alignments against a reference genome. See also <strong>BAM</strong> Format.</p><p><strong>SAMtools</strong>: widely used, open source command line tool for manipulating SAM/BAM files. Includes options for converting, sorting, indexing and viewing SAM/BAM files. The SAMtools distribution also includes bcftools, a set of command line tools for identifying and filtering genomics variants. Created by <a href="http://lh3lh3.users.sourceforge.net/">Heng Li</a>, currently of the Broad Institute.</p><p><strong>single-read sequencing</strong>: sequencing process where only one end of a DNA or RNA fragment is sequenced. Contrast with <strong>paired-end</strong> sequencing.</p><p><strong>VCF Format</strong>: Variant call format. Text file format for storing genomic variants, including single nucleotide polymorphisms, insertions, deletions and structural rearrangements. See also <strong>BCF</strong> format.</p><p><strong>Next</strong><strong>Generation</strong><strong>Sequencing</strong><br /> A high-throughput sequencing method which parallelizes the sequencing process, producing thousands or millions of sequences at once.</p><p><strong>Deep</strong><strong>Sequencing</strong><br /> Techniques of nucleotide sequence analysis that increase the range, complexity, sensitivity, and accuracy of results by greatly increasing the scale of operations and thus the number of nucleotides, and the number of copies of each nucleotide sequenced.</p><p><strong>Paired-End</strong><strong>Sequencing</strong><br /> Sequence both ends of the same fragment and keep track of the paired data.</p><p><strong>Adapter</strong><br /> Short oligonucleotides which are attached to the DNA to be sequenced. An adapter can provide a priming site for both amplification and sequencing of the adjoining, unknown nucleic acid.</p><p><strong>Library</strong><br /> A collection of DNA fragments with adapters ligated to each end.</p><p><strong>Bridge</strong><strong>Amplification</strong><br /> Generation of in situ copies of a specific DNA molecule on an oligo-decorated solid support.</p><p><strong>Emulsion</strong><strong>PCR</strong><br /> A method for bead-based amplification of a library. A single adapter-bound fragment is attached to the surface of a bead, and an oil emulsion containing necessary amplification reagents is formed around the bead/fragment component. Parallel amplification of millions of beads with millions of single strand fragments produces a sequencer-ready library.</p><p><strong>Alignment</strong><br /> Mapping of sequence reads to a known reference sequence</p><p><strong>Reference</strong><strong>sequence</strong><strong>/</strong><strong>genome</strong><strong>&nbsp; </strong><br /> A fully assembled version of a genome that can be used for mapping short DNA sequence reads for comparisons of genomes from various individuals</p><p><strong>Coverage</strong><strong>Depth</strong><br /> The number of nucleotides from reads that are mapped to a given position of reference genome.</p><p><strong>Specificity</strong><strong>&nbsp; </strong><br /> The percentage of sequences that map to the intended targets out of total bases per run.</p><p><strong>Uniformity</strong><strong>&nbsp; </strong><br /> The variability in sequence coverage across target regions.</p><p><strong>Homopolymer</strong><br /> Uninterrupted stretch of a single nucleotide type (e.g., TTT or GGGGGG)</p><p><strong>InDel</strong><br /> InDel stands for Insertion or deletion. A form of structural variation in which a DNA segment is either deleted or inserted.</p><p><strong>SNP</strong><strong>&nbsp; </strong></p><p>SNP stands for Single Nucleotide Polymorphism. A single base difference found when comparing the same DNA sequence from two different individuals.</p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28141/csbb-v10</guid>
	<pubDate>Wed, 29 Jun 2016 07:33:05 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28141/csbb-v10</link>
	<title><![CDATA[CSBB-v1.0]]></title>
	<description><![CDATA[<p>CSBB is a command line based bioinformatics suite to analyze biological data acquired through varied avenues of biological experiments. CSBB is implemented in Perl, while it also leverages the use of R and python in background for specific modules. Major focus of CSBB is to allow users from biology and bioinformatics community, to get benefited by performing down-stream analysis tasks while eliminating the need to write programming code. CSBB is currently available on Linux, UNIX, MAC OS and Windows platforms.</p>
<p>Currently CSBB provides 13 modules focused on analytical tasks like performing upper-quantile normalization on expression data or convert genome wide gene expression to z-scores when comparing expression data from different platforms.</p>
<p>More at&nbsp;https://github.com/skygenomics/CSBB-v1.0</p><p>Address of the bookmark: <a href="https://github.com/skygenomics/CSBB-v1.0" rel="nofollow">https://github.com/skygenomics/CSBB-v1.0</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28286/nipgr-hires-research-associate-jrf-laboratory-assistant</guid>
  <pubDate>Mon, 04 Jul 2016 20:12:14 -0500</pubDate>
  <link></link>
  <title><![CDATA[NIPGR Hires Research Associate, JRF, Laboratory Assistant]]></title>
  <description><![CDATA[
<p>National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg - Delhi, Delhi <br />₹15,000 a month<br />National Institute of Plant Genome Research (NIPGR) invites applications to recruit on vacant posts of Research Associate (RA), Junior Research Fellow (JRF) and Laboratory Assistant. Applications against these Sarkari Naukri can be submitted on or before 16 July 2016. <br />NIPGR Vacancy 2016 Details <br />1. Research Associate (RA) <br />Qualification: Ph.D. degree (awarded) in Molecular Biology/Biotechnolgy/Biochemistry/Plant Science/ Life Sciences/Bioinformatics or related field with 03 years post-doctoral research experience or 02 research papers in the journals of International repute are eligible to apply. Experience in the area of functional genomics, proteomics, metabolomics, multiomics and system biology will be preferred. <br />Age Limit: As Per Rules <br />2. Junior Research Fellow (JRF) <br />Qualification: M.Sc. degree or equivalent in Biotechnolgy/Biochemistry/Plant Science or Botany/ Life Sciences/Bioinformatics/ Molecular Biology or any other related field. Experience in advanced multiomics, big data analysis, molecular and system biology techniques will be given preference. <br />Age Limit: As Per Rules <br />3. Laboratory Assistant <br />Qualification: B.Sc. degree with 05 years working experience in government R&amp;D Laboratory assisting in the field of molecular biology and genomis. <br />Pay Scale: Rs.15000/- Per Month <br />Age Limit: As Per Rules <br />How to Apply : Duly filled-in applications in prescribed application format along with copies of required documents should be reach to: Dr. Subhra Chakraborty, Staff Scientist-VII, National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, P.O. Box NO. 10531, New Delhi – 110067 . The Last Date to submit application is 16 July 2016</p>

<p>Source: http://www.nipgr.res.in/careers/vacancies_latest.php#<br />Form at http://www.nipgr.res.in/files/careers/format_RA_JRF_LA.doc</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/28417/wisescaffolder</guid>
	<pubDate>Wed, 13 Jul 2016 08:08:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/28417/wisescaffolder</link>
	<title><![CDATA[WiseScaffolder]]></title>
	<description><![CDATA[<p>Function</p>
<p>WiseScaffolder is a stand-alone semi-automatic application for genome scaffolding of pre-assembled contigs using mate-pair data. It also produces editable scaffold maps, allowing either to build gapped scaffolds or usable as a common thread for the manual improvement of scaffolds.</p>
<p>Description&nbsp;</p>
<p>WiseScaffolder includes 4 subcommands: dumpconfig generates a configuration file that notably specifies the average insert size of the mate-pair library preprocess allows the detection and correction of chimerae, the estimation of contigs copy number and produces valuable outputs for the manual improvement of scaffolds scaffold constitutes the central scaffold-builder and comprises two modules:</p>
<p>i) the interative_scaffold_extender, which works with big, unambiguous contigs, or when they run out, single copy contigs, and</p>
<p>ii) the small_contig_inserter, which inserts the small contigs within scaffolds buildfasta converts the scaffold(s) map(s) into Fasta sequences.</p><p>Address of the bookmark: <a href="http://abims.sb-roscoff.fr/wisescaffolder" rel="nofollow">http://abims.sb-roscoff.fr/wisescaffolder</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28546/ra-bioinformatics-at-national-bureau-of-fish-genetic-resources</guid>
  <pubDate>Mon, 25 Jul 2016 03:14:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at  National Bureau of Fish Genetic Resources]]></title>
  <description><![CDATA[
<p>F.No. 1(16)/2016-Admn. (DBT-BBSRC Project)<br />Research Associate /JRF Biotechnology Job vacancies in National Bureau of Fish Genetic Resources on contract basis</p>

<p>Research Associate /01 Post</p>

<p>Essential: Ph.D. in Bioinformatics or 03 years research experience after Post Graduation in Bioinformatics with at least one research paper in Science Citation Indexed (SCI) journals.</p>

<p>Desirable:  The candidate should have at least 1st Division during Graduation and Post Graduation.  Experience in assembly/ analysis/ annotation of genomic/transcriptomic data generated on next generation sequencing platforms and working knowledge on different genomic softwares.  Publications in Relevant Field.</p>

<p>Pay Scale : Rs. 36,000/- +20% HRA </p>

<p>Age: 40 years for male and 45 years for female candidates, as on the date of interview</p>

<p>Junior Research Fellow/ 01 </p>

<p>Essential: Master Degree in Biotechnology/Life Science with Specialization in Molecular Biology with NET qualification. </p>

<p>Desirable:  Research Experience in Molecular Biology. 1st Division during Graduation as well as Post Graduation. Publications in Relevant Field.</p>

<p>Pay Scale: Rs. 25,000/-+ 20% HRA for 1st and 2nd year and Rs. 28,000/-+ 20% HRA for 3rd year</p>

<p>Age: 35 years for male and 40 years for female candidates, as on the date of interview.<br />How to apply<br />A walk-in-interview will be held on 26.07.2016 at 10:00 hrs. at ICAR-National Bureau of Fish Genetic Resources, Lucknow.</p>

<p>More at http://www.nbfgr.res.in/Recruitments.aspx</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/28564/dbt-%E2%80%93-bioinformatics-industrial-training-programme-biitp-2016-%E2%80%93-17</guid>
	<pubDate>Wed, 27 Jul 2016 04:09:59 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/28564/dbt-%E2%80%93-bioinformatics-industrial-training-programme-biitp-2016-%E2%80%93-17</link>
	<title><![CDATA[DBT – Bioinformatics Industrial Training Programme (BIITP) 2016 – 17]]></title>
	<description><![CDATA[<p>BIITP is a programme of Department of Biotechnology (DBT), Ministry of Science and Technology, Government of India, managed by Biotech Consortium India Limited (BCIL).The objective of BIITP is to provide an opportunity to bioinformatics students to acquire practical skills and experience by working on projects alongside industry experts as well as to provide an opportunity for the industry to identify potential employees.</p><p><strong>DBT Invites online applications from the bioinformatics&nbsp;students and requisitions from biotech/bioinformatics companies.</strong></p><p><strong>Biotech Industry</strong>&nbsp;:</p><p>Biotech/Bioinformatics companies interested to provide hands on industrial training to the students of Bioinformatics under BIITP may apply online. The companies would have no obligation towards any payments to trainees. The companies would be paid bench fee to cover expenses towards training. Trainees would be provided to companies subject to availability.</p><p><strong>Attn: Bioinformatics Students</strong></p><p>Bioinformatics students interested in training in biotech / bioinformatics companies may apply online.&nbsp;<strong>Stipend of Rs. 10,000/- per month</strong>&nbsp;will be paid to candidates placed for training. The candidates will be selected for training through an interview.</p><p><strong>Eligiblity</strong>&nbsp;:</p><p>a) B.E /B.Tech./M.Sc./M.Tech./Advanced Post Graduate Diploma in Bioinformatics from an Indian recognized university with minimum 55% marks or equivalent grade at highest degree/diploma completed in the year 2015 or 2016 are only eligible to apply.</p><p>b) The Advanced Post Graduate diploma should be of at least one year duration after graduation.</p><p>c)&nbsp; Students whose result of last semester/final year is not declared can also apply mentioning their marks upto the semester/year upto which result declared. The final result with original mark sheet(s) of all the semesters/years will have to be produced at the time of interview.</p><p><strong>Application Procedure</strong>&nbsp;:</p><p>The online application form is available below :</p><p><strong><a href="https://www.biotecnika.org/2016/07/dbt-bioinformatics-industrial-training-programme-biitp-2016-17/?xurl=%3A%2F%2Fwww.bcil.nic.in%2Fbiitp2016-17%2Fregistration1.asp" target="_blank">Application Form For Students (New User)</a></strong></p><p><strong><a href="https://www.biotecnika.org/2016/07/dbt-bioinformatics-industrial-training-programme-biitp-2016-17/?xurl=%3A%2F%2Fwww.bcil.nic.in%2Fbiitp2016-17%2Fregistration.asp%3FT1%3DCompany" target="_blank">Requisition form for companies (New User)</a></strong></p><p><strong><a href="https://www.biotecnika.org/2016/07/dbt-bioinformatics-industrial-training-programme-biitp-2016-17/?xurl=%3A%2F%2Fwww.bcil.nic.in%2Fbiitp2016-17%2Findex1.asp" target="_blank">Already registered User Click Here</a></strong></p><p>The following documents are to be sent to Mr. Manoj Gupta, Manager, Biotech Consortium India Limited, 5th floor, Anuvrat Bhawan, 210, Deen Dayal UpadhyayaMarg, New Delhi-110002.</p><p>More at&nbsp;http://www.bcil.nic.in/biitp2016-17/index.asp</p>]]></description>
	<dc:creator>Jit</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28592/bioinformatics-technical-position-at-cdac-pune-india</guid>
  <pubDate>Mon, 01 Aug 2016 03:36:26 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics Technical Position at CDAC Pune - India]]></title>
  <description><![CDATA[
<p>CDAC Pune Recruitment 2016 – Apply Online for Technical Positions: Department of Information Technology under the Ministry of Communications and Information Technology, Government of India, Centre for Development of Advanced Computing (C-DAC), Pune has advertised notification for the recruitment of Technical vacancies for for PwD candidates n direct recruitment basis. Eligible candidates can apply Online from 27-07-2016 at 10.00 AM to 31-08-2016 at 18.00 PM.. Other information like age limit, educational qualification, selection process &amp; how to apply are given below… </p>

<p>CDAC Pune Vacancy Details:<br />Total No. of Posts: 23 </p>

<p>Name of the Post: Technical </p>

<p>Name of the Discipline:<br />A. Computer Science/ Information Technology and Allied disciplines. </p>

<p>B.Electronics Communications/ Electrical/ Telecommunication/Instrumentation &amp; Control/ Medical Electronics/ Power Electronics/ VLSI &amp; Embedded System and Allied disciplines. </p>

<p>C.Biotechnology/ Bioinformatics/ Health informatics/ Geoinformatics/ Meteorology/ Environmental Science/ Ocean Sciences/Oceanography/Environmental Engineering </p>

<p>1. Visually Impaired: 09 Posts </p>

<p>2. Hearing Impaired: 08 Posts </p>

<p>3. Orthopedically Impaired: 06 Posts </p>

<p>Educational Qualification : Candidates should possess Graduation in relvany discpline with relevant experience. </p>

<p>Selection Process: Candidates will be selected based on applicants performance in interview. </p>

<p>How to Apply: Eligible candidates can apply online through the website www.cdac.in from 27-07-2016 at 10.00 AM to 31-08-2016 at 18.00 PM. </p>

<p>More at http://www.cdac.in/index.aspx?id=current_jobs</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/28819/research-project-at-iit-madras</guid>
  <pubDate>Wed, 17 Aug 2016 03:26:06 -0500</pubDate>
  <link></link>
  <title><![CDATA[Research Project at IIT, Madras]]></title>
  <description><![CDATA[
<p>Two project positions are available to work on (i) molecular modeling and molecular dynamics simulations and (ii) development of bioinformatics databases and tools at Protein Bioinformatics Lab, Department of Biotechnology, IIT Madras.</p>

<p>Duration : Initially for a period of one year. Extendable based on the performance.</p>

<p>Qualification: (i) MSc in Bioinformatics, Biotechnology, Physics, Biophysics, Biochemistry,Computer Science with NET (UGC/CSIR/GATE/BINC/INSPIRE etc) qualification. (OR) (ii) M. Tech in Bioinformatics, Biotechnology</p>

<p>Additional qualification: Programming skills</p>

<p>Candidates who fulfill the requirements of IIT have the possibility to register for PhD.</p>

<p>Fellowship: Rs.25,000 and HRA.</p>

<p>Applicants are encouraged to send the CV to the coordinator by postal mail and e-mail. The deadline to receive the applications is 31st August 2016. The project coordinator has the discretion to restrict the number of candidates to be called for interview to a reasonable limit on the basis of qualifications and experience higher than the minimum prescribed in the announcement.</p>

<p>Project Co-ordinator:</p>

<p>Dr. M. Michael Gromiha <br />Department of Biotechnology <br />Indian Institute of Technology Madras <br />Chennai 600036 <br />Email: gromiha@iitm.ac.in</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29017/walk-in-interview-jipmer</guid>
  <pubDate>Mon, 05 Sep 2016 04:01:13 -0500</pubDate>
  <link></link>
  <title><![CDATA[WALK-IN INTERVIEW @ JIPMER]]></title>
  <description><![CDATA[
<p>Department of Preventive and Social Medicine<br />, JIPMER, Puducherry –605006</p>

<p>WALK-IN INTERVIEW</p>

<p>JIP/PSM/INDO-US TB/ 2016/</p>

<p>Walk-in-interview for the following vacant posts funded by Department of Biotechnology, Govt.of India for the project entitled “Biomarkers for Risk of Tuberculosis and for Tuberculosis Treatment Failure and Relapse” in the Department of Preventive &amp; Social Medicine, JIPMER, Puducherry.</p>

<p>3. Technical Assistant</p>

<p>MCA/ MSc in Biostatistics/ MSc in Computational Biology from any recognized University @ Rs.23,220 1</p>

<p>Interested candidates may attend the walk-in interview with written screening test on 07, September 2016 at 9.30 A.M in the Dept. of Preventive and Social Medicine, IV Floor, Administrative Block, JIPMER.</p>

<p>The applicants are requested to bring the filled in application form and bio-data with original certificates for verification.</p>

<p>More Info: http://jipmer.edu.in/wp-content/uploads/2016/09/RECRUITEMENTsite-protocol-7.9.2016.pdf</p>
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