Bhubaneswar 751023

Advt No. 07/2016

Institute of Life Sciences (ILS), Bhubaneswar, an autonomous Institute of the Department of Biotechnology, Ministry of Science & Technology, Government of India engaged in advanced research invites applications from Indian nationals for the Ph.D. program. The main focus of the projects will be computational biology in the following areas.

S. No. Area of Research Principal investigator

1. Computational Cancer Biology Dr. Anshuman Dixit

2. Immunogenomics & Systems Biology Dr. Sunil Kumar Raghav

3. Chromatin remodeling and hematopoiesis Dr. Punit Prasad

Candidates are strongly encouraged to visit ILS webpage for detailed information, regarding the research activities of the above mentioned scientists.

Essential Qualifications:

(a) Eligibility: M.Sc., M.V.Sc., M.Pharm., M.S. Pharma. (with NET/GATE/GPAT/BINC/any other equivalent national level exam) or M.Tech with minimum of 60% marks (or equivalent grade point). Those awaiting final result may also apply.

Applications received after the last date will not be accepted. The envelope should clearly be superscribed with “Application for Ph.D. program (computational biology)”. Short-listed candidates selected for the interview will be published in the Institute website (www.ils.res.in).

Application Fees: Applicants except SC/ST candidates are required to send a non-refundable D.D. for Rs.100/- in favour of “Director, Institute of Life Sciences, Bhubaneswar” payable at Bhubaneswar along with duly filled-in application form by the date mentioned below. Director, ILS reserves the right to withdraw the procedure without assigning any reasons thereof.

Important dates: 

Last date of receiving applications: 24th June 2016 

Date of display of short-listed candidates and instructions on the Institute website: 30th June 2016 

Date of interview: The interview will be organized on 25th July 2016

Advertisement: https://www.ils.res.in/wp-content/uploads/2016/05/advt07-16.pdf

https://github.com/pditommaso/awesome-pipeline

Address of the bookmark: https://github.com/pditommaso/awesome-pipeline

More at https://github.com/neufeld/pandaseq

Address of the bookmark: https://github.com/neufeld/pandaseq

PEAR evaluates all possible paired-end read overlaps and without requiring the target fragment size as input. In addition, it implements a statistical test for minimizing false-positive results. Together with a highly optimized implementation, it can merge millions of paired end reads within a couple of minutes on a standard desktop computer.

More at http://www.exelixis-lab.org/web/software/pear

Paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3933873/

Address of the bookmark: http://www.exelixis-lab.org/web/software/pear

More at http://sfu-compbio.github.io/scalce/

Address of the bookmark: http://sfu-compbio.github.io/scalce/

Manual at http://spades.bioinf.spbau.ru/release3.7.1/manual.html

Address of the bookmark: http://bioinf.spbau.ru/spades

Address of the bookmark: http://busco.ezlab.org/

More at http://mrfast.sourceforge.net/manual.html

Address of the bookmark: http://mrfast.sourceforge.net/manual.html

Experience Required: 3-5 years of experience
No of Positions : Multiple
Qualifications: Candidates with minimum qualification as M.Sc Bioinformatics with 3-5 years of experience in Life sciences R&D or Pharma Industry.
Ph.D candidates with research experience in Bioinformatics with publications in International journal and minimum 2 years of industry experience in clinical genomics will be preferred for this position.

Requirement:

1. Must have basic understanding of molecular biology and Genomics.
2. Experience in application development or must have expertise in programming using either of Perl/Python.
3. Experience in statistical programming using R/Bioconductor/Matlab.
4. Strong concept in statistical and mathematical modelling.
5. Experience in designing and developing the bioinformatics pipeline.
6. Must have minimum 2+ years of hands on experience in NSG data analysis such as RNA-Seq,Exome-Seq ,Chip-Seq and downstream analysis.
7. Knowledge in WGS ,WES, Targeted re-sequencing,GWAS and population genomics will be preferred.
8. Must have experience working on opensource software/Framework and commercial software for NGS data analysis and reporting.
9. Should be aware of handling big data and guiding team members on multiple projects simultaneously.
More at http://www.ocimumbio.com/careers1/
10. Should have experience coordinating with different groups of clinical research scientist for various project requirements.
11. Ability to work as team as well as independently with minimal support.

Main features of YASS are:

• multiple, possibly overlapping seeds and a new hit criterion to ensure a good sensitivity/selectivity trade-off
• transition-constrained spaced seeds to improve sensitivity (transition mutations are purine to purine [A<->G] or pyrimidine to pyrimidine [C<->T])
• using different scoring schemes with bit-score and E-value evaluated according to the sequence background frequencies
• parameterizable output filter for low complexity repeats
• reporting of various alignment statistical parameters (mutation bias along triplets, transition/transversion)
• post-processing step to group gapped alignments

Address of the bookmark: http://bioinfo.lifl.fr/yass/