Interview Dates	28-29 August 2013, EMBL Grenoble
	28-30 August 2013, EMBL-EBI Hinxton
	28-30 August 2013, EMBL Hamburg
	29-30 August 2013, EMBL Monterotondo
	02-04 September 2013, EMBL Heidelberg

Spring Recruitment 2014

Call for applications for the Spring Recruitment 2014 is now open. Please apply here.

Information to applicants: The EMBL does not charge a fee at any stage of the recruitment process (application, interview meeting, processing, training or any other fees). The EMBL does not concern itself with information on bank accounts.

Application opens	12 August 2013 CET (GMT +1)
Registration Deadline	11 November 2013, 23:59 CET (GMT +1)  via the Online Application Form.
Submission Deadline	18 November 2013, 23:59 CET (GMT +1)
Reference Deadline	20 November 2013, 23:59 CET (GMT +1)
Interview Dates	Will be published closer to the time.
	Full details about the interview procedure will be sent only to invited candidates.

Reference Requirements

You can submit your application irrespective of the fact if your referees have completed the online reference form or not, as the submission does not impede referees access to the application.

Referees must submit their online references by latest 20 November 2013, 23:59 CET (GMT +1). We strongly suggest that you complete the 'general info' and 'references' part of the online application first in order to give your referees enough time to complete the reference online. Furthermore please make sure to contact your referees before completing this part in order to find out if they are available and willing to provide a reference. It is applicant's responsibility to ensure that references reach us on time.

As stated within the online application form we only accept references provided through institutional email accounts.

Only in cases where the referee does not have one, i.e. only holds a 'hotmail', 'gmail' etc. account, we ask you to:

1. Complete the form with the available email address.
2. Inform your referee NOT to complete the online form.
3. Ask your referee to send a reference letter on institutional headed paper as a PDF document topredocs@embl.de
4. Ask your referee to include your application ID number (5 digits) in the reference letter.

Read more @ EMBL

A new computational method for working out in advance whether a chemical will be toxic will be reporting in a forthcoming issue of the International Journal of Data Mining and Bioinformatics.

There is increasing pressure on the chemical and related industries to ensure that their products comply with increasing numbers of safety regulations. Providing regulators, intermediary users and consumers with all the necessary information to allow them to make informed choices with respect to use, disposal, recycling, environmental issues and human health issues is critical. Now, Meenakshi Mishra, Hongliang Fei and Jun Huan of the University of Kansas, in Lawrence, have developed a computational technique that could allow the industry to predict whether a given compound will be toxic even at a low dose and thus allow alternatives to be found when necessary.

Toxicity is almost always an issue of availability and dosage. Whether or not a compound is natural or synthetic it can be toxic from snake venom and jellyfish stings to petrochemicals and pesticides. However, some chemicals are more toxic than others, exposure to a lower dose will cause health problems or potentially be lethal. It is very important to find a way to determine whether a newly discovered synthetic or natural chemical might cause toxicity problems.

The team also points out that the US Environmental Protection Agency (EPA) and the Office of Toxic Substances (OTS) in the USA had listed 70,000 industrial chemicals in the 1990s, with 1000 chemicals added each year for which even simple toxicological experiments had not been carried out. This is largely a problem of logistics and costs as well as the ethical question of whether so many tests, which would have to be carried out on laboratoryanimals, should be done at all.

Now, Huan and colleagues in the Department of Electrical Engineering and Computer Science at Kansas, have successfully tested a statistical algorithm against more than 300 chemicals for which the toxicity profile is already known. Their technique offers a computational method of screening a large number of compounds for obvious toxicity very quickly and might preclude the need for animal testing of the compounds, provided regulators don’t insist on such “in vivo” data from the latter.

The research builds on well-established principles from the pharmaceutical industry known as Quantitative structure-activity relationships (QSARs) in which the type of atoms and how they are connected together can be correlated with the activity of a drug molecule. Certain molecular shapes and types are soluble in water, for instance, or interact in a certain way with different enzymes and other proteins in the body, leading to their overall activity. Different molecular features will make a similar molecule behave in a different way – more or less soluble, stronger or weaker acting. The team has now turned the QSAR around so that instead of searching for the features in a molecule that make it of benefit in medicine they look for the atomic groups and the type of bonds that hold them together to find associations with toxicity.

The team points out that few earlier attempts at predicting toxicity of chemicals have proved successful, most approaches are no better than random guessing. The team’s new statistical approach combines “Random Forest” selection with “Naïve Bayes” statistical analysis to boost the predictions well beyond random. They team saw prediction accuracy in 2 out of 3 chemicals tested. Given that there are around 100,000 industrial chemicals that need toxicity profiling, this result should allow the industry and regulators to focus on a large number of the most pressing of those, the ones predicted to have greatest toxicity and leave the less likely until additional resources are available.

The researchers are now tuning the algorithm to work faster and with greater precision so that it ignores common molecular features now known not to contribute to toxicity characteristics in the chemicals they have studied so far.

As Britney Spears asked in her song: “Don’t you know that you’re toxic?” Well, we do now.

“Computational prediction of toxicity” in Int. J. Data Mining and Bioinformatics, 2013, 8, 338-348

Source of the article 

Posted by ISCB Admin

F1000Research is an online life science journal, which enables articles to be updated post-publication, through the use of versioned papers. The journal is waiving all charges for bioinformatics software papers submitted before 31st December 2013. This is great news for both developers and users of bioinformatics tools; as incremental improvements and updates to software are released, these can be documented through a set of F1000Research-threaded papers.

F1000Research is novel in many of its approaches to science publishing. Once an article has passed editorial checks, publication is very fast, typically under 7 days following final submission. Articles undergo formal transparent peer-review, post-publication, with all reviews and any resultant discussion being documented as part of the article. The journal also requires all papers to include the underlying data, and all good science is accepted, regardless of perceived impact at time of publication.

The threaded papers approach enables developers to minimize the time spent on the important (but time consuming) job of disseminating documentation, whilst also demonstrating to funding bodies a commitment to ongoing engagement with users. Furthermore, it shows users that a tool is being actively maintained and improved.

To encourage bioinformatics tool developers to try this new way of publishing, F1000Research are waiving all article processing charges for such life science software papers submitted before the end of 2013. The fee waiver includes subsequent updates; just put the code SOFT13 in Section 6 of the simple one-page submission form. If you are using LaTeX to write papers, there is also a one-click submission option from the F1000Research LaTeX template, hosted by the online collaborative LaTeX editor writeLaTeX.

So how about providing an F1000Research threaded publication for your bioinformatics tool, allowing you to update the paper as you improve your software?

More information about F1000Research can be found at http://f1000research.com/
More information about threaded software papers can be found at http://blog.f1000research.com/2013/07/22/document-your-software-updates-with-f1000research/
The writeLaTeX F1000Research template can be found at https://www.writelatex.com/templates/41-f1000research-journal-article-template

URL: http://f1000research.com/

Contact Person: Michael Markie (michael.markie@f1000.com)

Posted by ISCB Admin

Applications are invited on prescribed format for the following assignment in a purely time bound research project undertaken in the Department of Life Science of the Institute.

1. Name of the Temporary Post :Junior research fellow- 01 Post

2. Name of the Research Project :“Deciphering role of cancer stem cell to therapy resistance in oral cancer”

3. Name of the Sponsoring Agency : SERB, DST, Govt. Of India.

4. Tenure of the Project : 03 years

5. Tenure of the Assignment : 03 years (based on the performance) or completion of the project.

6. Job Description : To carry out research work & experiments related to the project and

to continue Ph.D.

7. Consolidated monthly compensation / Fellowship : Rs.16,000/- P.M. (for 1st & 2nd year )

Rs.18,000/- P.M.(for 3rd year)

8. Essential Qualifications and experience : M.Sc./ M.Tech/ M.V.Sc (OR equivalent) in Life Science/ Microbiology/ Biochemistry/ Molecular Biology/ Immunology/

Biotechnology/Botany/Zoology/ Animal Science/ Bioinformatics or

related subjects with 60% of marks or 6.00 CGPA in 10 point scale.

GATE or NET of UGC/CSIR/ICMR/DBT (Lectureship/JRF) is mandatory.

9. Desirable Qualifications/ Experiences : Research experience in animal cell culture with knowledge in cancer biology, bioinformatics.

10. Accommodation : Bachelor accommodation in the hostel will be provided subject to

availability.

11. For technical information on the project, the candidate may contact the Principal Investigator at the following address with an updated Curriculum Vitae:

Name : Dr. Sujit Kumar Bhutia

Address : Dept. of Life Science

National Institute of Technology, Rourkela-769 008, Odisha

Telephone No : 0661-2464683, 0661-2462686.

E-mail : bhutiask@gmail.com, sujitb@nitrkl.ac.in

Eligible candidates may apply in the prescribed format

(http://www.nitrkl.ac.in/Jobs_Tenders/5ProjectFellowships/Default.aspx) affixed with two

nos.coloured photograph to be submitted in duplicate along with photo copies of relevant

certificates, grade/mark sheets, publications etc., to Asst. Registrar, SRICCE, National Institute of Technology, Rourkela–769 008 on or before 13.09.2013. The cover should be super- scribed clearly the post applied for & Name of the Project.Mere possession of minimum qualification does not guarantee invitation to the interview. Candidates will be short listed based on merit and need of the project.

Asst. Registrar (SRICCE)

Copy to : 1) All Heads of the Departments, NIT, Rourkela for publication Departmental Notice Boards.

2) Dr. S.K Bhutia, Principal Investigator with a request to give wide publicity to

advertisement.

3) Head of the Department, LS

4) Project file

5) Website: uploaded on 27.08.2013

Read more

1.       Research Scientist(Bioinformatics)

Work location: Shenzhen,China

Contact：bgicareer@genomics.cn

Responsibilities and description of the position

• The work involves the analysis, integration and visualization of a wide range of high and medium throughput data sets, including but not limited to luminex, flow cytometry, various next generation sequencing platforms and microarray.

•Will be expected to have a high level of proficiency in the application of bioinformatics analyses to real world data, and initiative regards keeping current with the latest developments in novel methods of analyzing/ visualizing biological data and applying those methods to the work at SIgN

Requirements for applicants：

• PhD in Bioinformatics or related field

• Fresh graduates and Postdocs with 3+ years of experiences are welcome

• Experience in one or more of database management, R coding or statistics

• Demonstrated accuracy, flexibility and integrity at work

• Good team player and independent researcher, self-driven with good interpersonal skills

2.       Research Scientist(Oncopathology)

Work location: Shenzhen,China

Contact：bgicareer@genomics.cn

Responsibilities and description of the position

•Emphasize on personalized medicine concept, which adheres to the P4 (predictive, preventive, personalized and participation) medical treatment theory

•Study on and integration of multi-omics and oncology related science and technologies

•Strive to clarify the genetic mechanisms of cancer development, discover biomarkers of differentiate molecular subtypes, and develop translated applications for clinical use

Requirements for applicants：

•Be familiar with the molecular, cellular, systems biology, and pathogenic mechanisms of cancer

•Have a strong interest in providing pathology support for drug and biomarker discovery programs in cancer

•Ph.D. in pathology or other related field, in addition to the MD degree will be highly desirable.

•Can interpret traditional diagnostic categories in the context of a detailed and current understanding of molecular and cellular biology.

3.       Research Scientist(Metagenome)

Work location: Shenzhen,China

Contact：bgicareer@genomics.cn

Responsibilities and description of the position

•Analysis and understanding all the health-related information from a genetic point-of-view, based on our knowledge about gene structures and gene functions, and its relationship with diseases, plus personal genomic messages.

•Construction of reference metagenome in human gut, construct the research platform, develope bioinformatics algorithms ,sequencing data assembly, annotation, variation study and function analysis.

Requirements for applicants：

•PhD in microbiology and molecular biology is required.

•A basic understanding of large data set analysis and programming is a plus

•With an interest in microbial ecology and hold top grades.

•Experience in one or more of metagenome, bioinformatics algorithms, metabonomics is advantageous.

4.       Research Scientist(Cancer Genome)

Work location: Shenzhen,China

Contact：bgicareer@genomics.cn

Responsibilities and description of the position

•Emphasize on personalized medicine concept, which adheres to the P4 (predictive, preventive, personalized and participation) medical treatment theory

•Study on and integration of multi-omics and oncology related science and technologies

•Strive to clarify the genetic mechanisms of cancer development, discover biomarkers of differentiate molecular subtypes, and develop translated applications for clinical use

Requirements for applicants：

•Ph.D. in molecular biology , genetics, oncology or other cancer disease.

•.Experience in one or more of cancer genome, bioinformatics, oncotherapy is advantageous.

•.With a strong interest in cancer biology.

Employer

• BGI

Website

• http://www.genomics.cn/

Read more

Description

Postdoctoral Associate in Machine Learning or Computational Biology

(http://www.dbmi.pitt.edu)

Elegibility: US Nationals only for NLM funded Postdoctoral Fellowship, and Any nationality for the other position.  Specialization in Machine Learning or computational biology with strong emphasis on computational aspects.

Employer: University of Pittsburgh Department of Biomedical Informatics

Faculty/Group: Madhavi Ganapathiraju, http://tonks.dbmi.pitt.edu/

Location:Pittsburgh, PA, United States

Type:Postdoctoral Associate

Ideal candidates would have ability to carry out independent research and a strong publication record. 

There is one slot for NLM funded Postdoctoral Research Associate position and one slot for NIH funded project for Machine learning & Computational Biology research.

Requirements:

- Post-graduate degree (MD or PhD) and training in Machine Learning or Computational Biology

- Ability to independently perform research in one of the above areas of biomedical informatics with mentoring from a faculty member.

- Ability to write and publish journal articles.

The University of Pittsburgh is an affirmative action, equal opportunity employer.

To apply

Apply online athttp://apply.dbmi.pitt.edu

and send CV tomadhavi+phds2@pitt.edu (yes +phds2 is part of the email address).

WEBSITE: http://www.dbmi.pitt.edu

DEPT SITE: http://www.dbmi.pitt.edu/madhavi

Description

A post-doctoral position is available in the group of Prof. Gaurav Pandey (http://www.mountsinai.org/profiles/gaurav-pandey) at the Mount Sinai School of Medicine in New York City. The group focuses on developing and applying machine learning methods to build network and predictive models of biological processes from large genomic data sets. Some of the specific areas my group is currently focusing on are the modeling of the immune response system, prediction of breast cancer phenotypes, and the discovery of novel therapeutics, especially synergistic drug pairs. These are important but quite difficult problems that need constant computational innovations, thus making the problems very interesting from a computer science perspective as well.

Our group is a part of the newly formed Institute of Genomics and Multiscale Biology (http://multiscale.mssm.edu) at Mt Sinai. The Institute aims to revolutionize the field of genomic medicine by bringing to the table skills from very unorthodox disciplines (for biology), such as computer science, statistics, physics and high-performance computing. The faculty members of the institute, experts in all these areas, analyze very large genomic data sets to build accurate predictive models of biological processes and complex diseases, such as cancer, type-2 diabetes and Alzheimer’s disease. Being positioned within a prominent medical center such as Mount Sinai makes it feasible to bring the predictions and therapeutic discoveries from these models to the patients’ bedside, thus placing the institute in a very unique position.

The selected candidate will be able to contribute to the ongoing projects in the group and the Institute, as well as define his/her own projects.

To apply

Candidates should have a recent PhD degree in a computationally-oriented field, and discipline and high motivation to pursue independent research in computational biology. Applicants are expected to have a solid background in programming and computational techniques, with a working knowledge of molecular biology and genetics. To apply, send a CV, a research statement and three reference letters to gaurav.pandey@mssm.edu.

WEBSITE: http://www.mssm.edu

DEPT SITE: http://multiscale.mssm.edu