Natural selection and other evolutionary forces lead to particular patterns of evolutionary dynamics, and they leave characteristic signatures on the genetic variation within populations. We use a combination of theory and experiments to study the dynamics and population genetics of natural selection in asexual populations such as microbes and viruses.

We use both theory and experiments to study evolutionary dynamics and population genetics, particularly in situations where natural selection is pervasive.

http://desailab.oeb.harvard.edu/home

Basic Sciences

Biotechnology & Bioinformatics

Qualifications are as per UGC norms. Please visit www.ugc.ac.in.

Educational, Age and experience requirements will be relaxed in exceptional cases.

Interested candidates are requested to apply with their complete CV with list of Publications, Patents, Industry and teaching experience at Undergraduate and Postgraduate level along with other relevant information to hr@tnu.in

Provide names and contact details of at least two references for confidential evaluation.

We follow Central University pay scales and few additional perks.

TNU follows highly liberal HR Policy with no salary constraint for exceptional candidates.

Applications are invited for the positions of - Professor, Associate Professor & Assistant Professor.
https://drive.google.com/file/d/0B0Y1Fpxmzyd3OHQ3aUNYa3hZY2c/view?usp=sharing

Reference
- Times of India, Ascent as on 20.04.2016.

Before you get started be sure to check out:

• devtools Google Group – https://groups.google.com/forum/#!forum/rdevtools
• book on “Advanced R programming” – http://adv-r.had.co.nz/
• GitHub repository – https://github.com/hadley/devtools

Address of the bookmark: https://www.rstudio.com/products/rpackages/devtools/

This page is a HOWTO guide for setting up a SLURM installation, currently focused on a CentOS 7 Linux OS. Please send feedback to Ole.H.Nielsen /at/ fysik.dtu.dk.

See the SLURM homepage (also https://computing.llnl.gov/linux/slurm/).

Address of the bookmark: https://wiki.fysik.dtu.dk/niflheim/SLURM

Monsanto is seeking a very talented Genomics Scientistto become an integral member of our Global Pipeline Analytics team with a focus on quantitative genetics. The ideal candidate will have familiarity with modeling and analysis of genetic data sets using a variety of statistical techniques.

Major Responsibilities:
- Provide guidance on experimental design for genomic-related experiments
- Familiarity with analysis of the following methods: GWS, QTL, eQTL, RNA-Seq
- Provide written and oral presentations of methods, results, conclusions, and recommendations to peer and management groups.
- Ensure timely delivery and clear communication of results
- Develop strong and successful collaborations among various Monsanto enabling teams.

Required Skills:

- PhD degree in Statistics, Biostatistics, Statistical Genetics, Quantitative Genetics, Breeding, Bioinformatics or a related field with 2 years of experience
- Working knowledge and experience with one of the following quantitative languages:R, Python, Perl, SAS
- Background in Windows and Linux operating systems
- Very strong problem solving skills will be required to work well as a member of a dynamic team
- Strong verbal and written communication skills.
- Demonstrated ability to deliver timely results and be results oriented.
- Extensive knowledge of quantitative genetics and experimental design. 
- Demonstrated track record of solving challenging and complex problems.

Desired Skills/Experience:

- Excellent communication skills, with the ability to summarize complex concepts in language understandable by scientists from a variety of disciplines.
- Experience in agronomy and/or plant breeding in vegetables or row crops.

Please apply to
https://jobs.monsanto.com/job/st-louis/genomics-scientist/769/2081771

http://biogps.org/#goto=welcome

Address of the bookmark: http://biogps.org/#goto=welcome

Address of the bookmark: http://www.ici.upmc.fr/cluego/

Calculate how much sequencing you need to hit a target depth of coverage (or vice versa).

Instructions: set the read length/configuration and genome size, then select what you want to calculate.

Written by Stephen Turner, based on the Lander-Waterman formula, inspired by a similar calculator written by James Hadfield. Coverage is calculated as C=LN/G and reads as N=CG/L where C = Coverage (X),L = Read length (bp), G = Haploid genome size (bp), and N = Number of reads. Source code on GitHub.

Address of the bookmark: http://apps.bioconnector.virginia.edu/covcalc/