Applications are invited for:

Junior Research Fellow, in a DBT funded project, is available in Translational Health Group, ICGEB, New Delhi

Qualifications:

Education: M.Sc. (preferably in Biotechnology, Life Sciences or Zoology, Chemistry, Bioinformatics). Candidates with hands on experience on GC-MS data acquisition and analysis will be given preference. Bioinformatics expertise required.

Fellowship: As per DBT guidelines.

Tenure: The position is purely on temporary basis with an initial tenure of six months and based on satisfactory performance may continue until the completion of the project.

Closing date for applications: 04/03/2017

Please send a "TWO PAGE" CV by email to: th.icgeb@gmail.com on or before the last date.

Research Associate, in a DBT funded project, is available in Translational Health Group, ICGEB, New Delhi

Qualifications:

Education: Ph.D. (in Biology, Biotechnology, Chemistry, Bioinformatics). Candidates with hands on experience on GC-MS data acquisition and analysis will be given preference.

Fellowship: As per DBT guidelines.

Tenure: The position is purely on temporary basis with an initial tenure of six months and based on satisfactory performance may continue until the completion of the project.

Closing date for applications: 04/03/2017

Please send a "TWO PAGE" CV by email to: th.icgeb@gmail.com on or before the last date.

Address of the bookmark: https://github.com/hugheslab/snpgenie

Usually, errors in PacBio reads include many insertions and deletions, and comparatively less substitutions. LoRDEC can correct errors of all these types.
After correction, a larger portion of the sequence of PacBio reads is usable for detection of region of similarity with other sequences, for aligning them to the contigs of an assembly, etc.

Why is LoRDEC different?

• It is efficient and can process large read data sets, included from eukaryotic or vertebrate species, on a usual computing server, and even works on desktop/laptop computers.
• It adopts a novel graph based approach: it builds a succinct De Bruijn Graph (DBG) representing the short reads, and seeks a corrective sequence for each erroneous region of a long read by traversing chosen paths in the graph.

Address of the bookmark: http://www.atgc-montpellier.fr/lordec/

Address of the bookmark: http://denbi-metagenomics-workshop.readthedocs.io/en/latest/index.html

Main features:

1. works with any number of scaffold assemblies in de-novo non-progressive fashion
2. allows to simultaneously work with scaffold assemblies obtained from any in silico and in vitro techniques, supporting multiple existing formats via built-in converters
3. creates an extensive report with several comparative quality metrics (both on assembly level and on the level of individual assembly points)
4. constructs a merged combined scaffold assembly
5. provides an interactive framework for a visual comparative analysis of the given assemblies

Address of the bookmark: https://cblab.org/camsa/

More at file:///home/urbe/Downloads/diamond_manual.pdf

http://www.nature.com/nmeth/journal/v12/n1/full/nmeth.3176.html

Address of the bookmark: https://github.com/bbuchfink/diamond

Our Research Team prides itself on driving cutting edge, industrial-scale
science to make an impact that belies the team’s size, in an environment
and culture that fosters creativity, innovation, collaboration, and fun.

More than 80% of our customers consent to participate in research, and as
a result of their participation, we have one of the largest recontactable,
genotyped, and phenotyped research cohorts in the world. The scope and
breadth of our vision means that most of the methods and tools necessary
to unlock the potential of this unique resource for discovery have yet
to be developed.

Our science has garnered the respect of many members of the
broader scientific community. For a list of our publications, see
www.23andme.com/publications/for-scientists/.

Join us! Visit our Careers page (www.23andMe.com/careers) to learn more
about these open positions:

• Scientist, Research Communications
• Bioinformaticist
• Computational Biologist, Ancestry R&D
• Scientist/Senior Scientist, Statistical Genetics
• Scientist/Senior Scientist, Survey Methodology
• Scientist/Senior Scientist, Health R&D
• Senior Computational Biologist
• Biostatistician

pfontanillas@23andme.com

Address of the bookmark: https://bioinfo.noble.org/GWASPRO/

ABACAS, that is able to contiguate contigs from a de novo assembly against a closely related reference.

IMAGE, an iterative approach for closing gaps in assembled genomes using mate pair information. It is able to close gaps left open by the assembler in a draft genome, even when using the same data sets as used by the original assembler.

iCORN, that enables errors in the consensus sequence to be corrected by iteratively mapping reads to the current assembly. An improved version, especially correction Pacfic Bioscience assemblies (PacBio) can be found here.

RATT, a tool to transfer the annotation from a reference genome, or an earlier assembly, onto the latest assembly.

PAGIT bundles these software and makes them more accessible for users.

Address of the bookmark: http://www.sanger.ac.uk/science/tools/pagit

http://www.disi.unige.it/person/MasulliF/ricerca/PhDinGenova2017.html

The call for some funded positions for the 3 years PhD studies at the Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS) in Genova is available at

http://www.studenti.unige.it/postlaurea/dottorati/XXXIII/ENG/

The deadline for applications is June13, 2017 and the PhD courses and fellowships should start on Nov 2017.

Details for the application to the PhD Program in Computer Science and Systems Engineering (CODICE 6608) are at http://phd.dibris.unige.it/csse/index.php/how-to-apply

The research activity of my research group is focused on Computational Intelligence, Machine Learning, Bioinformatics, Systems Biology, and Positive Technology as described at http://www.disi.unige.it/person/MasulliF/ricerca/index.html

The research themes proposed by me and Prof. Stefano Rovetta are:

- Computational Intelligence and Machine Learning (see http://www.disi.unige.it/person/MasulliF/ricerca/Phd2017-T1.html)

- Computational Intelligence and Health and Wellbeing Support( see http://www.disi.unige.it/person/MasulliF/ricerca/Phd2017-T3.html)

You can also propose a different research theme belonging to the research activity of my group.

Looking for self-motivated PhD candidates, interested to the mathematical aspects of their research and to the development of new algorithms for intelligent data analysis, and skilled in programming and in thorough experimental data analysis. They will be part of my research group and will collaborate to our research projects and publications.

Italian and international students interested to work are invited to send their cv and the name/email-addresses of 3 referees to my email address francesco.masulli@unige.it A.S.A.P.