Email: admin@niab.org.in Telephones: +91 40 2304 9403 Telefax: +91 40 2304 2740
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About NIAB National Institute of Animal Biotechnology (NIAB), Hyderabad, an autonomous institute under the aegis of Department of Biotechnology, Government of India, is aimed to harness novel and emerging biotechnologies and create knowledge in the cutting edge areas for improving animal health and productivity.

Applications are invited for the following temporary research positions to work in ongoing DBTBBSRC sponsored research project entitled “Transcriptome Analysis in Indian buffalo and the Genetics of Innate Immunity” at the National Institute of Animal Biotechnology, Hyderabad.

(A) Project Scientist – Level B (One Position)

Emoluments: Rs. 15600 + GP Rs. 5400 + 30 % HRA p.m. (Total emoluments will be Rs. 49,770/-p.m. for the duration of the project)

Essential Qualification: Candidates having M.V.Sc. in Veterinary Microbiology / Veterinary Pathology / Veterinary Public Health / Ph.D. degree in Life Sciences, Biotechnology, Molecular Biology or any other related field from the recognized university are eligible to apply.

The candidate should have a good academic record and research experience as evidenced from published in standard referred journals / patents.

Desirable: Candidates having research experience in the area of tissue culture, genomics, Transcriptomics and Advanced Molecular Biology will be given preference.

Age Limit: Not exceeding 30 years as on last date of the submission of the application.

(B) Research Associate in Bioinformatics (One position)

Fellowship: Rs. 22,000 + 30 % HRA

Essential Qualification: Candidates having Ph.D. degree or M.Tech. with three years of
experience in Bioinformatics, Computational Biology, Biotechnology, Life Sciences or any other related field are eligible to apply.

Desirable: Candidate having research experience in the area of next generation sequencing (NGS) data analysis, Genome wide association studies, Genomic selection, advance genomic data analysis etc., will be given preference. The candidate should have a good academic record and research experience as evidenced from published papers in standard journals / patents.

Age Limit: Not exceeding 30 years as on last date of the submission of the application.

Project Duration: The duration of the project is Three years and the positions are co- terminus with the duration of the project. (Initial appointment will be for one year and further extension will be granted based on annual review).

Mode of submission of application: Only online applications are to be submitted through
www.niab.org.in on or before 08 December, 2014. Link for online submission of applications will be available from 10 November 2014.

Advertisement: www.niab.org.in/Notifications/Advt_5_2014/Advt_5_2014.pdf

Address of the bookmark: http://christophergandrud.github.io/d3Network/

Applications are invited along with complete bio-data and attested copies of certificates of qualifications, experience etc. for the one post of Research Fellow and one post of Program Assistant under PURSE Grant of the University in Centre for Systems Biology & Bioinformatics, UIEAST, Panjab University, Chandigarh which is tenable till the period of
the project.

Essential Qualification

For Research Fellow:-

M.Sc. in Systems Biology and Bioinformatics / Life Sciences with minimum 55% marks.

Preference will be given to NET/GATE/ICMR qualified candidates without fellowship however, candidates who have cleared the Panjab University Ph.D. entrance test in Systems Biology & Bioinformatics will also be eligible.

For Program Assistant:-

The candidate must have M.Sc./M.Tech/MCA/PGDCA in Computer Science and must be able to handle LAN, Linex. Preference will be given to the candidate having experience in
System Administration.

Emoluments

For Research Fellow Rs. 12,500/- per month (Fixed)
For Program Assistant Rs. 12,500/- per month (Fixed)

Applications should be reach on or before 19-11-2014 in the office of the undersigned.

Interview will be held on 21-11-2014 in the office of the Coordinator, Centre for Systems Biology & Bioinformatics, South Campus, Block-3, Sector-25, Panjab University, Chandigarh. No TA/DA will be paid.

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What Is Julia Language?

Julia is a programming language that came into the limelight in 2012. It is a general-purpose programming language that was designed for solving scientific computations. Julia was meant to be an alternative to Python, R and other programming languages that were mainly used for manipulating data. This is because it has numerous features that can minimize the complexities of numerical computations. 

Julia optimizes on the best features of Python and R while at the same time overlooks their weaknesses. This explains why it is viewed as an alternative to these programming languages. For instance, it utilizes the readability and simplicity of Python then performs faster.

Julia is the most preferred programming language for data scientists and mathematicians. This is because its core features are similar to the ones that are used on most data software. Also, the language is ideal for these two subjects because its syntax is similar to the standard mathematical formulas.

Key Features Of Julia Language
Uses JIT Compilation
Parallelism
Dynamic Typing
Simple Syntax
Allows Metaprogramming
Accessible to Libraries
-1-Array Indexing

Julia Vs Python And R Programming Languages
1. Speed
Julia is faster than both Python and R. This is a very critical aspect that is given special attention in the big data programming. The high speed of Julia is because of JIT compilers. You will need to install external libraries on Python to achieve similar speed.

2. Syntax
Julia has a math-friendly syntax. The syntax of this programming language is similar to the mathematical formulas hence can be used to perform mathematical and scientific computations. This syntax makes it easier to learn than Python.

3. Parallelism
Although both Python and R use parallelism, Julia uses a top-level parallelism. Julia allows the processor to perform to the optimum level than what Python and R can achieve.

4. Versatility
Julia programming language is more versatile than Python and R. It allows a programmer to move from different codes and functions with ease.

The only area that Python and R are superior to Julia is in terms of community. Given that Julia is a new programming language, it has a small community as compared to others which have been around for years.

In overall Julia programming language is a better alternative that you can use to handle Big data projects. Despite having a small community, it is one of those programming languages that you can easily learn.

Address of the bookmark: http://www2.decipher.codes/

For further details about the original technique see the UpSet website. You can also check out the UpSetR shiny app. Here is the source code for the shiny wrapper.

A Python package called py-upset to create UpSet plots has been created by GitHub user ImSoErgodic.

Address of the bookmark: https://github.com/hms-dbmi/UpSetR/

Specifically, the taxonomy() function implemented in myTAI can be used to classify genomes according to phylogenetic classification into Phylostrata (Phylostratigraphy) or to retrieve species specific taxonomic information when performing Divergence Stratigraphy (see Introduction for details).

Address of the bookmark: https://cran.r-project.org/web/packages/myTAI/vignettes/Taxonomy.html

Originally design to map the location of objects in a 10 km map IrishGrid includes:

• native support of the Irish Grid System (see http://www.osi.ie/)
• optimize for speed (there's as less as possible data to conversion)
• customized color functions

https://code.google.com/p/irishgrid/downloads/detail?name=irishgrid.pl

Address of the bookmark: https://code.google.com/p/irishgrid/

If you want to know, how Docker works, and why you should consider using Docker, please take a look at the Docker website.

Address of the bookmark: https://www.docker.com/why-docker