kallisto

(Deemed University)

Hamdard Nagar, New Delhi – 110 062

R E C R U I T M E N T

(Advertisement No. 5/2014)

Applications on prescribed form are invited for filling up the following teaching positions in the Department of Biotechnology, Faculty of Science in the university. Eligible candidates may apply on or before 30.09.2014.

1. Professor/Associate Professor - One in Pay Band of Rs. 37400-67000+ AGP Rs.10000/9000

2. Assistant Professor - Two in Pay Band of Rs. 15600-39100+ AGP Rs. 6000/-

ASSISTANT PROFESSOR – 02 (including 01 SFS)

Specialization : Bioinformatics

Qualification and Experience :

Ph.D. in Biotechnology or an allied discipline with M.Sc. in Biotechnology/ Biochemistry in the First division or equivalent grade from a recognized University/ Institute.

NET in Life Science or allied discipline in addition to the above qualification.

Experience : At least two years of Post-doctoral teaching and/or research experience in Bioinformatics or relevant field in a UGC recognized Institution of repute or international research institute/ University. Proof of research to be evidenced by publications in SCI-indexed journals of high impact factor as the first or corresponding author.

Note : University may consider exempting candidates from NET, who has been awarded Ph.D. degree from ‘A’ Grade accredited University following the procedure as notified by the UGC in its Regulations of 2009 and adopted by Jamia Hamdard.

For more information: http://www.jamiahamdard.ac.in/PDF/Online%20application%20form%20_Teaching_1.pdf
http://www.jamiahamdard.ac.in/PDF/PBAS.pdf

Online version and downloadable software package for offline use (source code in PERL) freely available at http://bat.ina.certh.gr/tools/circoletto/

Contact:ndarz@certh.gr

Address of the bookmark: http://tools.bat.infspire.org/circoletto/

Functional and Comparative Genomics

http://jp.senescence.info/
http://www.senescence.info/
http://www.liv.ac.uk/integrative-biology/staff/joao-de-magalhaes/

• Import of mapped data from mapped data (BAM/SAM/bowtie etc)
• Creation of data groups for visualisation and analysis
• Visualisation of mapped regions against an annotated genome.
• Flexible quantitation of the mapped data to allow comparisons between data sets
• Statistical analysis of data to find regions of interest
• Creation of reports containing data and genome annotation

Address of the bookmark: http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/

Extent of employment: 30 Hours per Week
Duration of employment: 1st of October 2015 to 30th of September 2019
Gross monthly salary and pay grade in terms of collective agreement for university staff (payable 14 times per year): B1, € 1.997,20

Responsibilities
The successful candidate (f/m) will pursue a Ph.D. project related to the interpretation of plant genome and transcriptome sequencing data from next-generation sequencing (NGS) platforms. In particular, the candidate will characterize the unexplored genome of quinoa, a crop plant of long-standing tradition in Latin America. We collaborate with research partners in Austria and abroad, and the candidate’s project will be of central importance in the context of this research network.

Required skills and qualifications
We are looking for a graduate student (f/m) with a Master’s degree in bioinformatics or in a related field, solid programming skills (e.g. developing sequence analysis tools), experience with the analysis of NGS data sets, understanding of lab methods and knowledge of genomics/transcriptomics. The group has successfully performed several projects using NGS technology. We have recently published the reference genome sequence of sugar beet (Dohm et al., Nature, 2014), a crop plant closely related to quinoa (same family, but different genus). Not yet published is a quinoa genome assembly that we have generated, and which will serve as the starting point of the candidate’s project. We are a multidisciplinary team and offer work in a lively and friendly atmosphere, and state-of-the-art computing infrastructure. We are looking forward to expanding our team by a dedicated and strongly motivated person with a distinct interest in the challenges of plant genomics.

Applications can be submitted until: 16th of August 2015

University of Natural Resources and Life Sciences Vienna seeks to increase the number of its female faculty and staff members. Therefore qualified women are strongly encouraged to apply. In case of equal qualification, female candidates will be given preference unless reasons specific to an individual male candidate tilt the balance in his favour.

Please send your job application (incl. letter of motivation, CV, summary of Master’s thesis and contact details for two referees) to Personnel department, University of Natural Resources and Life Sciences, 1190 Vienna, Peter-Jordan-Straße 70; E-Mail: kerstin.buchmueller@boku.ac.at. (Reference code: 59)

We regret that we cannot reimburse applicants travel and lodging expenses incurred as part of the selection and hiring process.

www.boku.ac.at

http://ggdc.dsmz.de/ggdc_background.php#

Genome-to-Genome Distance Calculator 2.1

http://ggdc.dsmz.de/ggdc.php

Address of the bookmark: http://ggdc.dsmz.de/

• Updated human gene set (GENCODE 21)
• Updated rat gene set including manual annotation from HAVANA
• New species: Vervet-African green monkey
• Imported Transcript Support Levels (TSLs) from UCSC for human and mouse
• Imported APPRIS flag for human and mouse
• Updated Amazon molly gene set

Find more at http://www.ensembl.info/blog/2014/10/02/ensembl-77-has-been-released/

Address of the bookmark: https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082

Orange Bioinformatics provides access to publicly available data, like GEO data sets, Biomart, GO, KEGG, Atlas, ArrayExpress, and PIPAx database. As for the analytics, there is gene selection, quality control, scoring distances between experiments with multiple factors. All features can be combined with powerful visualization, network exploration and data mining techniques from the Orange data mining framework.

Address of the bookmark: https://pypi.python.org/pypi/Orange-Bioinformatics/2.5.34