WALK-IN-INTERVIEW

The following vacancies shall be filled purely on adhoc basis under Non-Institutional adhoc project “Bioinformatics in ICMR Institutes” funded by Indian Council of Medical Research at Vector Control Research Centre, Puducherry, to be renewed annually and filled through Walk-in-Interview as indicated below. Candidates who wish to appear for the Walk-in-Interview can download the application format given in the website of Vector Control Research Centre (www.vcrc.res.in). Duly filled in application along with attested copies of certificate should be submitted at time of interview.

Date & Time : 05.12.2013 at 9.00 AM – Scientist-C (Non-Medical)

05.12.2013 at 1.30 PM – Scientist-B (Non-Medical)
06.12.2013 at 9.00 AM – Technical Assistant (Research Assistant)
06.12.2013 at 1.30 PM – Multi Tasking Staff (General)

Place : Vector Control Research Centre, Puducherry

Project entitled : Biomedical Informatics Centres of ICMR

1. Scientist - C (Non-Medical) Number of post – ONE

Essential qualification

B.E./ B. Tech. Degree in Bioinformatics/ Computational Biology from a recognized University with 6 years experience in the relevant field OR

First class Master’s Degree and Ph.D. Degree in Bioinformatics/ Computational Biology from a recognized University OR

First class Master’s Degree in Bioinformatics/ Computational Biology from a recognized University with 4 years R & D experience in the related subjects as mentioned above OR

Second class Master’s Degree + Ph.D. in Bioinformatics/ Computational Biology from a recognized University with 4 years research experience in bio-medical subjects

Age: Not exceeding 40 years Consolidated Salary – Rs.39,960/- p.m. + HRA as
admissible

Desirable qualification (i) Post-doctorate in Bioinformatics/ Computational Biology or M.E. / M. Tech. Degree in Bioinformatics/ Computational Biology from a recognized University for candidates with First Class relevant degree.

(ii) Additional post-doctoral research / teaching experience in Bioinformatics/Computational Biology in recognized Institute(s).

(iii) Knowledge of computer applications or data management

Job requirements i) To apply Bioinformatics / Computational Biology tools in understanding interactions between vectors and parasites/ pathogens and target based development of drug / insecticides.

ii) To assist the investigators to carry out genomic studies on parasites/pathogens/vectors of vector borne diseases

Advertisement: http://vcrc.res.in/Adv_Bio13.pdf

Address of the bookmark: http://www.biostat.jhsph.edu/~iruczins/teaching/

The Law group provides internal Institute-specific development, training and support roles for data manipulation, sequence analysis and any other aspect of the analysis of biological data using computer systems. Additionally we provide databases and applications supporting the international animal science community, particularly tools and resources for genome mapping.

Head: Andy Law. Members: John Bowman (animal facility database applications), Zen Lu (bioinformatics support), Trevor Paterson (software development)

More @ http://www.bioinformatics.ed.ac.uk/groups/roslin-bioinformatics-group

However, nanopore sequencing is an emerging and rapidly developing technology. It is not clear what will be most informative. We hope that IONiseR will provide a framework for visualisation of metrics that we haven’t thought of, and welcome feedback at mike.smith@embl.de.

If you’re not interested in the quality assement of the raw or event level data, and want to jump straight to the getting FASTQ format files from fast5 files you can go straight to the final section of this document.

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/IONiseR/inst/doc/IONiseR.html

Novel diagnostic platform for detection of Osteoarthritis

I invite applications from highly motivated individuals to join my laboratory as a PhD student in Systems Biology at the University of Calgary McCaig Institute for Bone and Joint Health. This project is aimed at characterizing the networks of physical (protein-protein) interactions underlying inflammatory processes in patients with Osteoarthritis and how this differs from patients with Rheumatoid Arthritis and normal individuals. This work will eventually lead to the development of a novel diagnostic platform for the non-invasive and accurate detection of early Osteoarthritis. The selected candidate will use state-of-the-art computational methodologies to systematically analyze proteomic data, and develop /implement new algorithms to identify protein and functional interaction networks from high throughput experimental data. The individual will also benefit by working closely with experts at the UofC and UofA through an AIHS Alberta Osteoarthritis Team Grant which includes experts from all pillars of health research. The candidate will also be supported to attend bioinformatics workshops and conferences to advance and disseminate their research.
Qualifications: The ideal candidate will have a Master’s degree in Computational Biology, Bioinformatics, or equivalent with strong background knowledge of the Biological Sciences, Biochemistry, and Microbiology. The individual should additionally have experience in handling high-throughput data sets as well as programming skills. The candidate will be registered as a PhD student in Dr. Krawetz’s laboratory, located in the new state-of-the-art Health Research Innovation Centre at the UofC. The individual will have strong verbal and written skills and the ability to work efficiently in a team environment.

In addition to the outstanding research opportunities available in this setting, students also enjoy the many cultural and sporting amenities provided in the city of Calgary, and can take advantage of the unparalleled skiing and hiking in the Rocky Mountains that are less than an hour away.

Candidates must be academically competitive and will be expected to apply for external funding. The stipend is $25,000/yr. For outstanding PhD students, internal top-up award opportunities are available on a competitive basis. If interested in joining the lab, please contact Dr. Krawetz directly at rkrawetz@ucalgary.ca and provide the following information:

- Short cover letter explaining your interest in the lab
- Resume
- Scanned copy of transcript or listing of course grades
- Names and contact information for two individuals who will be willing to provide letters of reference

Address of the bookmark: http://christophergandrud.github.io/d3Network/

- Development of computational methods to investigate the interplay between epigenetic and genetic layers and their role in tumor progression, by integrating genomic, epigenomic and transcriptional data. PI: Mattia Pelizzola (http://tiny.cc/comEpi)
- Epigenome and transcriptome analysis in mouse models of Hepatocellular Carcinoma. PI: Bruno Amati - Small and long non-coding RNAs in cancer stem cells. PI: Francesco Nicassio

All projects will benefit from the availability of both in-house and publicly available next-generation sequencing datasets. Familiarity with Linux environment, programming skills (especially in R) and a background in either computational biology, or physics/engineering/math will be advantageous.

Deadline for the application January 6th, to apply: http://genomics.iit.it/resources.html

Start date: March 1st, 2014

Duration: 1+2 years

Contact Person (Referent): Mattia Pelizzola

Ref. E-Mail: mattia.pelizzola@iit.it

Tel: 0039-02-94375058
Group Web Page: http://genomics.iit.it

What Is Julia Language?

Julia is a programming language that came into the limelight in 2012. It is a general-purpose programming language that was designed for solving scientific computations. Julia was meant to be an alternative to Python, R and other programming languages that were mainly used for manipulating data. This is because it has numerous features that can minimize the complexities of numerical computations. 

Julia optimizes on the best features of Python and R while at the same time overlooks their weaknesses. This explains why it is viewed as an alternative to these programming languages. For instance, it utilizes the readability and simplicity of Python then performs faster.

Julia is the most preferred programming language for data scientists and mathematicians. This is because its core features are similar to the ones that are used on most data software. Also, the language is ideal for these two subjects because its syntax is similar to the standard mathematical formulas.

Key Features Of Julia Language
Uses JIT Compilation
Parallelism
Dynamic Typing
Simple Syntax
Allows Metaprogramming
Accessible to Libraries
-1-Array Indexing

Julia Vs Python And R Programming Languages
1. Speed
Julia is faster than both Python and R. This is a very critical aspect that is given special attention in the big data programming. The high speed of Julia is because of JIT compilers. You will need to install external libraries on Python to achieve similar speed.

2. Syntax
Julia has a math-friendly syntax. The syntax of this programming language is similar to the mathematical formulas hence can be used to perform mathematical and scientific computations. This syntax makes it easier to learn than Python.

3. Parallelism
Although both Python and R use parallelism, Julia uses a top-level parallelism. Julia allows the processor to perform to the optimum level than what Python and R can achieve.

4. Versatility
Julia programming language is more versatile than Python and R. It allows a programmer to move from different codes and functions with ease.

The only area that Python and R are superior to Julia is in terms of community. Given that Julia is a new programming language, it has a small community as compared to others which have been around for years.

In overall Julia programming language is a better alternative that you can use to handle Big data projects. Despite having a small community, it is one of those programming languages that you can easily learn.

The course topics will include theoretical and practical aspects in:
- Genomes comparisons,
- Evolutionary analyses (orthologs, paralogs and ancestral genomes
inference),
- RNAseq and Next Generation Sequencing (including algorithms, methods
and sequence mapping tools, data analyses and applications).

The course programme will be centred on theoretical presentations
followed by practical sessions. Practical sessions in a Linux
environment will involve Unix shell and Perl scripting. Participants
are assumed to be familiar with this environment.

A series of lectures delivered by prominent scientists on recent hot
topics in genome (Viruses, Prokaryotes, Eukaryotes) studies will be
included in the programme and future research perspectives will be
highlighted.

The topics that will be included in the course programme are similar
to those included in previously organized courses:http://www.pasteur.fr/~tekaia/BGA_courses.html

The course is aimed at motivated Ph.D students and Post-Doctoral
Researchers in Academic Institutions, with background in Mathematics,
Statistics, Biology or Computer Science and who are involved in
Bioinformatics and Genomes studies.

Selection of participants will be based on their background, running
research projects and on expressed motivations.
Selected students will have free accommodation and meals and are
expected to contribute with 200 euros and to pay for their travel
expenses.
All participants (students and invited speakers) will stay in the same
hotel.

Detailed indications are available on the course web site: http://events.embo.org/14-comparative-genomics/index.html

Candidates are advised to complete carefully the application form,
together with an abstract of at least one of their running projects, a
"one-page CV" and a personal Identity Picture (Photo).

The application deadline is March 14, 2014.

The organizers:
Menelaos Manoussakis, Hellenic Pasteur Institute, Athens, Greece.
Evdokia Karagouni, Hellenic Pasteur Institute, Athens - Greece.
Evie Melanitou, Institut Pasteur Paris - France.
Fredj Tekaia ( Institut Pasteur Paris France)
URL: http://www.pasteur.fr/~tekaia/BGA_courses.html

Date: 5 – 17 May, 2014.
More at http://events.embo.org/14-comparative-genomics/index.html
will take place in the ,

Address of the bookmark: http://www2.decipher.codes/