For informal enquiries please contact Anne Walsh via email: anne.walsh@bristol.ac.uk.

Apply at http://www.bris.ac.uk/jobs/find/details.html?nPostingID=3639&nPostingTargetID=13346&option=28&sort=DESC&respnr=1&ID=Q50FK026203F3VBQBV7V77V83&JobNum=ACAD101624&Resultsperpage=10&lg=UK&mask=uobext

Desirable qualification: M.Sc (Life Sciences) with Bioinformatics knowledge and hands on molecular biology tools.

Age: Not exceeding 30 years on the last date of receipt of application

Job work: Molecular modelling studies, Database curation, Metagenomic studies on Dengue virus

Advertisement: http://vcrc.res.in/writereaddata/BIPrj15.pdf

In fact, there are huge demands for expert biological data analyst. It’s a fairly new  (not exactly) hot area, these bioinformatician are invaluable because they know and understand the significance of biological data for your research and how you can use it for better understanding of biological problems.

The bioinformatics can discover biological patterns and stories in genomic and proteomics data. They can develop the pipeline needed to properly collect, store and analyse it.

Once your research group is ready to make a larger investment and hire a bioinformatician to gain a competitive edge, there are several key traits to seek out in potential candidates. The best bioinformatician are:

1. Highly Skilled - programming skills, experience with the biological software and tools.

The biological data won’t illuminate much if the scientist analysing it doesn’t possess practical programming skills, experience with the biological software and tools and a thorough understanding of basic biological stuff. A solid background in mathematics and statistics is also an indispensable trait.

2. Insight - Real vision, robust understanding and deep insight.

In order to hire the best bioinformatics and computational biologist scientist for your needs, it is always recommended and mostly practiced by the recruiters, to ask each contender to write and develop a sample script/presentation based on a specific set of data you provide. Then, explore the approaches used to deal with data provided and pick up those candidates who convey real vision, robust understanding and deep insight.

3. Energetic – Curiosity to explore

Mostly natural curiosity and enthusiasm for solving big biological problems coupled with an ability to transform data into a scientific stories may place one candidate above the rest. In addition to achieve that, the bioinformatician should be agile enough to quickly modify their methods to suit changes within a particular research.

4. Researcher – Publications

Look for someone who has a keen sense and understanding of concern biological problems. You can judge it by looking at previously published papers and data. It is always recommended to have a look at GitHub and other repository for codes written by her/him.

5. Impressive communicator - Insight that can’t be expressed is worthless.

Good bioinformatics scientists are able to uncover biological patterns and are willing to explain those patterns in clear and helpful ways through thoughtful and open communication. In other words, they should must have good scientific writing skills. A computational biologis/bioinformatician  should know how to present the data and tell a scientific story through numbers/images.

1) demonstrated experience in Bioinformatics research,
2) programing experience (python and/or R, C and C++ are very welcome),
3) knowledge of Linux/Unix environment,
4) experience in handling deep-seq data,
5) highly motivated and hard working, and
6) interested to work with a multi-disciplinary team combining bioinformatics, genomics, computational biology approaches with experimental biology.

Our research interest covers different areas of bioinformatics and genomics in order to achieve a deeper understanding of gene and genome structure and function (please look at our PubMed publications for more details about our research http://www.ncbi.nlm.nih.gov/pubmed/?term=pesole+g).

Interested applicants should email the curriculum vitae to Prof. Graziano Pesole at graziano.pesole@uniba.it or Dr. Ernesto Picardi at Ernesto.picardi@uniba.it.

Start date: immediate

Duration: up to 24 months
Contact Person (Referent): Ernesto Picardi
Ref. E-Mail: ernesto.picardi@uniba.it
Tel: +390805443308
Fax: +390805443317

Group Web Page: http://www.pesolelab.it/

Project Assistant II Jobs opportunity in National Chemical Laboratory (NCL) on temporary basis

Project Code No. : GAP312626

Title of the Project : Microbial ecology and distribution of geochemical cycling genes in an hot spring ecosystem

No. of Post : 01

Qualifications : M.Sc./B.Tech/M.Tech in Computational biology/ Bioinformatics from recognized university with minimum 60 % marks (aggregate)

Desirable : Good knowledge of computational skills, Linux (command line and GUI) and Unix; Perl / Python / R /C-programming. Practical knowledge of analysis of Next generation sequence datasets (amplicon sequencing, whole metagenome, and complete genome sequencing) with reference to microbes. Analysis and statistical validation of NGS data generated from different chemistry platforms. Some wet-lab experience in microbial system would be an added advantage as project involves some travel.

Emoluments : Rs. 16,000/-

Age Limit : 28 years
How to apply

The application with the above information duly signed together with photo-copies of relevant certificates/testimonials should be addressed to : The Head, NCIM Resource Centre (Attn Dr. M.S. DHARNE), National Chemical Laboratory, Pune 411 008, so as to reach on or before 16th November 2015.

More at http://www.ncl-india.org/files/JoinUs/JobVacancies/TemporaryJobs.aspx?menuid=ql6&childmenustripid=divSubQL6

Sponsored/CSIR Networked Project:
(i) Genomics and Informatics Solutions for Integrating Biology (GENESIS)" [BSC-0121] (up to March, 2017).
(ii) Profiling and characterization of early phase differential mi-RNA (s) responsible for downstream developmen of insulin resistance in hMSC derived adipocytes. (GAP-0188) [up to 31.03.2018].

Position: Project Fellow (2 position)
Age : 28 years as on 18.12.15
Salary : Rs.12,000/- P.M.
Rs.14,000/- P.M.
as per the funds provisions in the respective projects.
Eligibility Criteria : 1st Class B. Tech. in Bioinformatics/ Computational Biology
OR
M.Sc. in Bioinformatics/ Computational Biology with 55% marks
OR
M.Tech. in Bioinformatics/ Computational Biology with 55% marks
OR
M.Sc. in any field of Life Science with Diploma in Bioinformatics

Selection Procedure : Walk In Interview

Date : 18 Dec , 2015
Time : 10:00 A.M.
Venue : CSIR-IHBT Palampur (H.P.)

Eligibility : MSc(Bio-Informatics), BE/B.Tech

Location : Kasaragod

Last Date : 20 Dec 2015

Hiring Process : Face to Face Interview
Central University of Kerala

JRF job opportunity in Central University of Kerala (CUK) on temporary basis

Project Title : "Targeting TAL effector mediated susceptibility for durable and broad-spectrum resistance to bacterial blight in Rice"

No. of Post : 01

Qualification : MSc in any subject under Life Science or Bioinformatics/ B.Tech in Bioinformatics + 1 yr experience

Stipend : Rs. 14,000/-
How to apply

Interested candidates are requested to send their applications explaining their interest in the position with an updated CV to Dr. Ginny Antony, Assistant Professor, Department of Plant Science, School of Biological Sciences, Central University of Kerala, Padannakkad, Kasaragod, Kerala - 671 314 email: ginnycuk2013@gmail.com on or before 20th December, 2015.

https://www.pmgenomics.ca/hoffmanlab/

The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available.

Database URL: http://www.ensembl.org.

Address of the bookmark: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/

More at http://busco.ezlab.org/

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