Spines

http://www.broadinstitute.org/science/programs/genome-biology/spines

Address of the bookmark: http://www.broadinstitute.org/science/programs/genome-biology/spines

HiCdat is easy-to-use and provides solutions starting from aligned reads up to in-depth analyses. Importantly, HiCdat is focussed on the analysis of larger structural features of chromosomes, their correlation to genomic and epigenomic features, and on comparative studies. It uses simple input and output formats and can therefore easily be integrated into existing workflows or combined with alternative tools.

More at http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0678-x

Address of the bookmark: https://github.com/MWSchmid/HiCdat

More at http://hgdownload.cse.ucsc.edu/admin/exe/

Address of the bookmark: http://hgdownload.cse.ucsc.edu/admin/exe/

http://millslab.org/research.html

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

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.

No of Vacancies: 01
Pay Scale: Rs. 9300-34800 + Grade Pay Rs. 4600/-

Educational Qualification and Experience: (From Recognized University / Institute) M.Sc. in Biotechnology, Molecular Biology, Human Genomics / Biochemistry / Biophysics.

Age Limit: 18-50 years

Please see Detailed Advertisement Link for full info: https://drive.google.com/file/d/0Bz3xO6e_7OeeZllINnRyWlN5UFE/view

· Enzyme immobilization supports for select enzyme systems.

· New tools for microbial strain and genome engineering using
state-of-the-art methodologies.

· Rapid high throughput assays to screen microorganisms from various
sources for enzymatic activities of interest.

· High throughput combinatorial approaches to the formulation of growth
media in support of microbial enrichments, strain isolations and growth
optimization.

· Meta-transcriptomics for the discovery of new enzymes.

· Strain adaptation techniques in defined chemostat environments for
microbial strain development.

The internships are based at the Experimental Station R&D Center in
Wilmington, DE.

If interested, apply fast!

For more information and to apply, go to:

http://careers.dupont.com/jobsearch/job-details/industrial-biosciences-summer-internship/008549W-10/

SLURM is similar in many ways to most other queue systems. You write a batch script then submit it to the queue manager. The queue manager then schedules your job to run on the queue (or partition in SLURM parlance) that you designate. Below we will provide an outline of how to submit jobs to SLURM, how SLURM decides when to schedule your job and how to monitor progress.

SLURM has a number of valuable features compared to other job management systems:

• Kill and Requeue SLURM’s ability to kill and requeue is superior to that of other systems. It waits for jobs to be cleared before scheduling the high priority job. It also does kill and requeue on memory rather than just on core count.
• Memory Memory requests are sacrosanct in SLURM. Thus the amount of memory you request at run time is guaranteed to be there. No one can infringe on that memory space and you cannot exceed the amount of memory that you request.
• Accounting Tools SLURM has a back end database which stores historical information about the cluster. This information can be queried by the users who are curious about how much resources they have used.

Summary of SLURM commands

The table below shows a summary of SLURM commands. These commands are described in more detail below along with links to the SLURM doc site.

Address of the bookmark: https://github.com/dentearl/mafTools