INB

Software developer position

admin — Wed, 27 Mar 2013 05:02:08 +0000

A Software Developer position is currently available in my laboratory at EMBL Grenoble. You will find the details in the link below or at www.embl.org/jobs

http://www.embl.fr/aboutus/jobs/searchjobs/index.php?newlang=1&newms=sr&searchregion=670

Location:   Grenoble, France
Staff Category:   Staff Member
Contract Duration:   1 year
Grading:   4, 5 or 6, depending on experience and qualifications
Closing Date:   07 April 2013
Reference number:   GR_00052

Deadline Extension SNP-SIG ISMB/ECCB 2013

admin — Fri, 22 Mar 2013 04:01:22 +0000

We would like to remind you that the third edition of the SNP satellite
interest group (SIG) meeting at ISMB/ECCB 2013
will take place July 19th, 2013 at the main conference venue in Berlin,
Germany.
We have an exciting program planned for the event including keynote talks,
invited presentations, a roundtable
discussion and a poster session.
The general themes of the SIG will be:

*Databases, data mining algorithms and visualization tools for SNP analysis

*Methods for predicting regulatory/structural/functional impacts of SNPs

*Personal Genomics, GWAS studies and SNP prioritization

*Population genomics and phylogenetic analysis

We welcome presentation proposals and poster abstract submissions.
More information about the conference is available here:
*http://snpsig.biofold.org/*

The call for submissions is OPEN:
http://snpsig.biofold.org/abstract.html
The deadline for the submission of Presentation Proposals and Posters
has been extended to April 15th 2013.

We look forward to seeing you in Berlin.

Sincerely,
Yana Bromberg and Emidio Capriotti

**************************************
Dr. Yana Bromberg
Assistant Professor, Department of Biochemistry and Microbiology
School of Environmental and Biological Sciences
Lipman Hall 218
Rutgers University, New Brunswick, NJ 08901
E-mail: YanaB@rci.rutgers.edu
Phone: +1 646 220-3290
web: http://aesop.rutgers.edu/~dbm/ybromberg.html

Emidio Capriotti
Division of Informatics
Department of Pathology
University Alabama at Birmingham
619 19th st. south, WP Building, Suite P220
Birmingham, AL 35249, USA
e-mail: emidio@uab.edu
Phone: +1 205 975 2928
Fax: +1 205 934 5499
web: http://biofold.org/emidio

The Automated Function Prediction, an ISMB 2013 Special Interest Group meeting.

admin — Mon, 18 Mar 2013 03:57:45 +0000

Key Dates:

April 20, 2013: Deadline for submitting extended abstracts posters & talks
May 9, 2013: Notifications for accepted abstracts e-mailed to corresponding authors
May 16, 2012: Deadline for presenters to confirm acceptance of invitation to speak.
July 20, 2013: AFP SIG preceding ISMB/ECCB 2013, Berlin

Sequence and structure genomics have generated a wealth of data, but extracting meaningful information from genomic information is becoming an increasingly difficult challenge. Both the number and the diversity of discovered sequences are increasing, and the fraction of genes whose function is known is decreasing. In addition, there is a need for annotation which is standardized so that it could be incorporated into function annotation on a large scale. Finally, there is a need to assess the quality of the available function prediction software.

For these reasons and many more, automated protein function prediction is rapidly gaining interest among computational biologists in academia and industry.

The Automated Function Prediction Special Interest Group (AFP SIG) has been part of ISMB since 2005. We call upon all researchers involved in gene and protein function prediction and annotation, both computational and experimental, to submit an abstract to the AFP meeting. Authors of select abstracts will be invited to give a talk and/or present a poster.
We will also be discussing the upcoming second Critical Assessment of Function Annotations, or CAFA. CAFA 1 was a highly successful experiment, engaging 30 groups worldwide, and has resulted in 16 peer-reviewed papers in Nature Methods and BMC Bioinformatics:
http://www.nature.com/nmeth/journal/v10/n3/full/nmeth.2340.html

http://www.biomedcentral.com/bmcbioinformatics/supplements/14/S3

We are looking forward to a new and expanded CAFA 2 in 2013-2014, which will include a cellular component prediction track, and a human-specific track.

Keynote speakers:
Patricia Babbitt, University of California, San Francisco
Alex Bateman, European Bioinformatics Insitute
Anna Tramontano, “La Sapienza” Universtiy, Rome.

For further instructions on AFP 2013, please go
here: http://BioFunctionPrediction.org

We are looking forward to seeing you in Berlin!

Iddo Friedberg, co-chair, on behalf of the AFP 2013 organizing committee

Contact: afp.cafa.2013@gmail.com

Computational approaches to networks, cells and tissues. Registration is closed

admin — Sat, 16 Mar 2013 03:52:47 +0000

Organizers: James Sharpe (CRG) and Hernán López-Schier (Helmholtz Zentrum München)

The aim of this meeting is to bring together leading scientists working on data-driven computational modelling, with a common interest in unraveling the fundamental mechanisms that govern cell and tissue biology. Because this field of research is still budding, it is essential to exchange ideas and train the next generation of researchers to join the field. A key challenge is to cope with multiscale systems. In other words, it is increasingly recognized that many levels of organization must be treated as equally important, in particular: the molecular, cellular and tissue levels. We have thus selected speakers working at each of these different levels. These pioneers, from around the world, are each combining quantitative data and computer modeling, and in some cases, pursuing projects which are already combining the different levels into unified models.Speakers:

Alexander AULEHLA, Developmental Biology, European Molecular Biology Laboratory (EMBL), Heidelberg DE
Javier BUCETA, Theoretical and In Silico Modeling of Biological Systems Group (The.Si.M.Bio.Sys.), Parc Científic de Barcelona, Barcelona ES
Rico COEN, John Innes Centre, Norwich Research Park, Norwich UK
Miki EBISUYA, Graduate School of Medicines, Kyoto University, Kyoto JP
Niels GRABE, Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, University Heidelberg, Heidelberg DE
Jeremy GREEN, Department of Craniofacial Development, King’s College London, London UK
Veronica GRIENEISEN, Computational & Systems Biology, John Innes Centre, Norwich Research Park, Norwich UK
Shigeru KONDO, Graduate School of Frontier Biosciences, Osaka University, Osaka JP
Lucia MARUCCI, Gene Regulation, Stem Cells and Cancer Programme, Centre for Genomic Regulation (CRG), Barcelona ES
Juan Manuel PEDRAZA, Physics Department, University of the Andes, Bogotá CO
Stanislav SHVARTSMAN, The Department of Chemical and Biological Engineering, Princeton University, Princeton (NJ) US
Gürol SÜEL, Section of Molecular Biology, Division of Biological Sciences, UC San Diego, San Diego US
Fabian THEIS, Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München and Institute of Mathematical Sciences, Technische Universität München, Munich DE

Venue
PRBB Auditorium
Dr. Aiguader 88
08003 Barcelona
Spain

Registration:

Registration is now closed.CALL FOR POSTERS
We invite participants to present abstracts for the poster session, which will be held on 10 April (schedule will be confirmed in the final program of the meeting). Please upload your text document (doc, docx, rtf, txt) when registering. Deadline for presenting posters and registering: 15 March 2013 at 15:00h.
On 20 March we will send an email to all the authors with the list of accepted posters.

Contact person:
Blanka Wysocka
CRG – Centre for Genomic Regulation
Dr. Aiguader, 88
08003 Barcelona, Catalonia, Spain
Tel.: +34 93 316 01 45
blanka dot wysocka at crg dot eu

Activity Supported By:

QuanTissue: QuanTissue represents a multi-disciplinary project whose main objective is to bring together experts from complementary disciplines with a firm interest in a quantitative understanding of the basic mechanisms that govern morphogenetic processes at subcellular to tissue levels. It has become evident that imaginative and refined experimental strategies based on genetics, imaging, quantitative and biophysical approaches, combined with the exploration of the fullest potential of mathematical modeling are necessary to understand cellular and developmental biology. QuanTissue is an interactive and collaborative network to bridge the gap between traditionaldevelopmental cell biology, biophysics and systems biology.

European Science Foundation: The European Science Foundation (ESF) provides a platform for its Member Organisations to advance science and explore new directions for research at the European level. Established in 1974 as an independent non-governmental organisation, the ESF currently serves 78 Member Organisations across 30 countries.

Critical Assessment of Genome Interpretation (CAGI)–Open Challenges and Conference

admin — Sun, 03 Mar 2013 02:21:13 +0000

Following is an omnibus update on CAGI, including new information about the CAGI conference in July and the recently added anonymity policy. Follow our Twitter feed @CAGInews.

The Critical Assessment of Genome Interpretation (CAGI) is a community experiment to assess computational methods for predicting the phenotypic impacts of genomic variation. The current CAGI experiment has eight open challenges, available on the CAGI website: https://genomeinterpretation.org/

In the CAGI experiment, participants are provided genetic variants and make predictions of resulting phenotypes. Independent assessors then evaluate these predictions against experimental characterizations. The primary goals of the experiment are to establish the current state of the art, identify bottlenecks in genome interpretation, inform critical areas of future research, and connect researchers from diverse disciplines whose expertise is essential for advancing methods for interpreting genomic variation.

The deadline for current CAGI predictions is 28 March 2013. Anonymous submissions, with limitations, are allowed this year. https://genomeinterpretation.org/content/anonymity-policy We encourage use of both established methods and experimental approaches, and we welcome predictors of all backgrounds.

The current CAGI experiment will culminate in a conference in Berlin, on 17-18 July 2013, immediately before the ISMB SIGs. An NHGRI R13 grant will help support travel and participation in the meeting. https://genomeinterpretation.org/content/cagi-2012-conference

Previous CAGI experiments have highlighted striking breakthroughs as well as disappointing failures. Publications from the previous CAGI are underway; slides and posters presentations about CAGI may
be found at: https://genomeinterpretation.org/content/cagi-presentations The results from the current CAGI challenge will be published as well.

The currently open CAGI challenges are:

+ Seventy-seven PGP genomes (provided by George Church). Challenge: Predict clinical phenotypes from genome data, and match individuals to their health records. https://genomeinterpretation.org/content/PGP2012

+ Exomes of Crohn’s disease patients and healthy individuals (provided by Andre Franke). Challenge: predict which individuals have Crohn’s. https://genomeinterpretation.org/content/new-crohns-dataset

+ Exomes from two families with lipid metabolism disorders (provided by John Kane and Pui-Yan Kwok). Challenge: predict lipid profiles and a causative variant. https://genomeinterpretation.org/content/FCH https://genomeinterpretation.org/content/HA

+ Variants in DNA double-strand break repair genes (provided by Sean Tavtigan). Challenge: predict probability of each variant occurring in a breast cancer case versus healthy control. https://genomeinterpretation.org/content/MRN

+ Mutations in p53 gene exons affecting mRNA splicing (provided by Jeremy Sanford). Challenge: predict how variants impact splicing. https://genomeinterpretation.org/content/Splicing-2012

+ Variants of a p16 tumor suppressor protein (provided by Silvio Tosatto). Challenge: predict how well variants inhibit cellproliferation. https://genomeinterpretation.org/content/p16_2012

+ Shewanella oneidensis MR-1 gene disruptions (provided by Adam Arkin). Challenge: Predict impact of microbial gene disruptions on cell growth under stress conditions https://genomeinterpretation.org/content/MR-1_2012

+ riskSNPs disease-associated loci (provided by John Moult). Challenge: identify potential causative SNPs. https://genomeinterpretation.org/content/risksnps2012

We are also soliciting challenges for the next CAGI. Please contact us at mailto:cagi@genomeinterpretation.org with proposals for suitable datasets.

In order to access the current challenges and submit predictions for CAGI, please register at https://genomeinterpretation.org/.

Registered users also have access to presentations from the previous CAGI conferences, as well as posters and talk slides that summarize the results.

Sincerely,

Daniel Barsky, CAGI 2012 Organizer
Steven E. Brenner, CAGI Chair
John Moult, CAGI Chair

cagi@genomeinterpretation.org

Postdoctoral position in Statistical Physics / Biological Physics / Computational Biology in Paris

admin — Sun, 03 Mar 2013 02:14:39 +0000

We are seeking candidates for a 1+1-year postdoctoral fellowship in the interface between statistical physics, biological physics and computational biology, in the team “Statistical Genomics and Biological Physics” at the Laboratoire de Genomique des Microorganismes, Universite Pierre et Marie Curie, Paris, France. The research will be done in tight collaboration with Alexander Schug (Karlsruhe Institue for Technology, Germany) and Olivier Tenaillon (INSERM, Paris, France), about integrating structural and co-evolutionary information in protein modeling.

Applicants are expected to have a strong background in one or more of the following fields: Statistical physics, biological physics (in particular biomolecular simulation), statistical inference, bioinformatics, computational biology, (soft-)condensed matter theory, machine learning; they should have some programming knowledge and a
general interest in molecular biology. Prior experience with biological systems and data analysis is welcome, but not required.
Applicants must be interested in collaborating with researchers of different scientific background, ranging from theoretical physics via biomolecular simulation to experimental biology.

For further information, please contact Martin Weigt (martin.weigt@upmc.fr). Applications including a CV, a list of publications, a research statement and addresses of at least two potential reviewers are to be sent before March 31, 2013, as one
single pdf file to the same e-mail address.

–
Martin Weigt
Laboratoire de Génomique des Microorganismes, UMR 7238
Université Pierre et Marie Curie
15, rue de l’École de Médecine
75006 Paris, FRANCE

Tel: +33 (0)1.44.27.73.68
Fax: +33 (0)1.44.27.73.36
Email: martin.weigt@upmc.fr
http://sites.google.com/site/martinweigt/

Curso de Bioinformática y Biología Computacional. Escuela Complutense de Verano 2013

admin — Sat, 02 Mar 2013 05:51:03 +0000

OBJETIVOS:

Adquirir conocimientos elementales del sistema operativo Linux, de programación en Perl y de diseño e implementación de bases de datos relacionales. Linux, como otros sistemas operativos emparentados con Unix, es la plataforma preferida para el desarrollo y el uso de aplicaciones Bioinformáticas, Perl es un lenguaje de programación frecuentemente usado para el desarrollo de pequeñas aplicaciones bioinformáticas y las bases de datos relacionales son sistemas estandar de almacenamiento, análisis y consulta de datos.

Familiarizarse con los tipos de datos que son objeto de análisis en la Bioinformática, y con las bases de datos en que dichos datos están almacenados y cómo se accede ellas a través de la Internet.

Conocer los tipos de herramientas y las estrategias generales de investigación usadas más frecuentemente en Bioinformática. Este objetivo es muy amplio y abarca técnicas y métodos enfocadas a analizar y comparar secuencias de ácidos nucléicos, analizar y anotar genomas, predecir y comparar la estructura y la función de proteínas, diseñar fármacos optimizados para su interacción con centros activos de enzimas o receptores o con ácidos nucleicos, etc.

PROGRAMA:

Los temas principales a tratar serán:

Introducción a la Bioinformática.
Nociones sobre el uso de computadores con sistema operativo tipo Linux
Programación básica con Perl.
Nociones sobre bases de datos relacionales y servicios Web.
Bases de Datos en Bioinformática.
Herramientas y conceptos de análisis de secuencias de acidos nucléicos.
Herramientas y conceptos de análisis de secuencias de aminoácidos.
Predicción de estructura secundaria y terciaria de proteínas.
Filogenia.
Arrays de DNA y análisis de datos.
Proteómica y Bioinformática.

ACTIVIDADES PRÁCTICAS:

Este cursos es fundamentalmente práctico. Todas las clases se impartirán en un aula de informática donde se realizaran ejercicios directamente por los alumnos. Las clases contemplan una breve introducción teórica o metodológica seguida de la actividad práctica por cada alumnos.

DURACION DEL CURSO:

El curso propuesto es de 15 jornadas de 5 horas, que corresponden a 75 horas totales.

HORARIO DEL CURSO:

El horario previsto es de 9:00 a 14:00. En general, se impartirán dos clases por jornada, con una duración de entre dos y tres horas por clase.

Del 8 al 26 de julio.

Más información

Matricula on-line

Computational Molecular Evolution

admin — Sat, 23 Feb 2013 05:27:01 +0000

Next Session:

Jun 24th 2013 (10 weeks long)

Workload: 7-9 hours/week

This course is about molecular evolution – the evolution of DNA, RNA, and protein molecules. The focus is on computational methods for inferring phylogenetic trees from sequence data, and the course will cover the fundamental theory and algorithms, while also giving the student hands-on experience with some widely used software tools. Since evolutionary theory is the conceptual foundation of biology (in the words of Theodosius Dobzhansky: “Nothing in biology makes sense except in the light of evolution”), what you learn on this course will be relevant for any project you will ever do inside the life sciences. A phylogenetic tree will almost always help you think more clearly about your biological problem.

A special emphasis is put on methods that employ explicit models of the evolutionary process (maximum likelihood and Bayesian approaches), and we will explore the role of statistical modeling in molecular evolution, and in science more generally. A mathematical (statistical) model of a biological system can be considered to be a stringently phrased hypothesis about that system, and this way of thinking about models will often be helpful. In addition to model-based methods, you will also learn about other approaches, such as those based on parsimony and genetic distance (e.g., neighbor joining).

Often, the evolutionary tree is the result we are interested in – knowing how a set of sequences (or organisms) are related can provide us with important information about the biological problem we are investigating. For instance, knowing which organisms are most closely related to a newly identified, uncharacterized, pathogenic bacterium will allow you to infer many aspects of its lifestyle, thereby giving you important clues about how to fight it. In other cases, however, inferring the structure of the tree is not the goal: for instance, our main focus may instead be the detection of positions in a protein undergoing positive selection (indicating adaptation) or negative selection (indicating conserved functional importance). However, even in these cases, the underlying phylogenetic tree will be an important part of our hypothesis about (model of) how the proteins have been evolving, and will help in getting the correct answer.

Although the study of molecular evolution does require a certain level of mathematical understanding, this course has been designed to be accessible also for students with limited computational background (e.g., students of biology).

Topics covered:

Brief introduction to evolutionary theory and population genetics.
Mechanisms of molecular evolution.
Models of DNA and protein substitution.
Reconstruction of phylogenetic trees using parsimony, distance based methods, maximum likelihood, and Bayesian techniques.
Advanced models of nucleotide substitution (gamma-distributed mutation rates, molecular clock models, codon models and analysis of selective pressure).
Statistical analysis of biological hypotheses (likelihood ratio tests, non-parametric and parametric bootstrapping, Bayesian statistics).

Course Syllabus

Week 1:   Introduction to evolutionary theory and population genetics: models of growth, selection and mutation
Week 2:   Neutral mutations, genetic drift and tree reconstruction by parsimony
Week 3:   Consensus trees and distance matrix methods
Week 4:   Mini-project I
Week 5:   Models of DNA and protein evolution
Week 6:   Likelihood methods
Week 7:   Bayesian inference of phylogeny
Week 8:   Mini-project II
Week 9:   Testing hypotheses in a phylogenetic context
Week 10:  Bootstrap, jackknife, and permutation tests

Recommended Background

Basic molecular biology (important)
Basic mathematics (less important, but student should not be afraid of math – the course has been designed to be accessible also for biology students)
Knowledge of UNIX is not required but will be helpful (exercise manuals will introduce the subject gradually, and we will provide links to self-help resources)

Course Format

The course will consist of lectures, quizzes, handout exercises, computer exercises and two mini-projects. Quizzes and handout exercises are used both to test student knowledge and as a pedagogical tool for putting focus on key aspects of the theory. The student will acquire practical experience in the use of a range of computational methods and programs by analyzing sequences from the scientific literature and by using their own data during the mini-projects. As part of the mini projects, students will use peer grading.

FAQ

Will I get a Statement of Accomplishment after completing this class?Yes. Students who successfully complete the class will receive a Statement of Accomplishment signed by the instructor.

About the Instructor

Anders Gorm Pedersen Technical University of Denmark (DTU)

Bioinformatician at Ontario Institute for Cancer Research.

admin — Wed, 20 Feb 2013 05:46:49 +0000

Position: Bioinformatician
Site: MaRS Centre, Toronto
Department: Informatics and Biocomputing
Reports To: Manager, Data Coordination Centre (DCC)
Salary: Commensurate with level of experience
Hours: 35 Hrs/week
Status: Full-time, Permanent

The Ontario Institute for Cancer Research (OICR) is seeking a bioinformatician work with the International Genome Consortium’s (ICGC) Data Coordination Centre (DCC).

The International Cancer Genome Consortium is a global research effort working to comprehensively describe genomic, transcriptomic and epigenomic changes in 50 different cancer types or subtypes of clinical and societal importance. It is one of the largest genomics efforts in the world today and has enjoyed significant international media coverage in addition to publications in high impact journals.

The Ontario Institute for Cancer Research hosts the ICGC’s Data Coordination Center (DCC) whose staffs are responsible for enabling global access to the project’s data.
The ICGC DCC Curation team currently has an opportunity for an experienced bioinformatician with a strong background in genomics to join our efforts in enabling translational research by improving the accessibility and utility of this cancer genomics data.

QUALIFICATIONS

Background in genomics (to include transcriptomics and epigenomics) with minimally 3 years of working experience in bioinformatics and genomics; relevant graduate school experience will be considered
Strong working experience in a Unix or Linux environment
Strong interest in helping us achieve the goals of the ICGC project
Strong skills in scripting language(s) (Perl and/or Python)
Exceptional attention to details
Excellent communication skills; as required for collaborating with scientists from various disciplines and parts of the world
Ability to use issue tracking and wiki software (eg: Jira and Confluence) in day-to-day work process
Affinity for a service and production-oriented work environment
Worked with high-throughput genomics data of the types produced in a genome centre (with a large number of projects and NGS sequencers)
Knowledgeable on current genomics methods, data standards and tools
Played a key role in a collaborative genomics project with members from multiple institutions
Participated in a project with public data and web resource components
Worked closely with both wet-lab (data-producing) and informatics scientists
Has a record of contributing to peer-reviewed scientific publications in the areas of bioinformatics and genomics
Collaborate with a global community of cancer genomics researchers
Facilitate the collection and delivery of high quality cancer genomics data
Contribute to efforts in useful application and interpretation of this data

OICR is an innovative cancer research institute located in the MaRS Centre in the Discovery District in downtown Toronto. OICR is addressing significant challenges in cancer research with multi-disciplinary, multi-institutional teams. New discoveries to prevent, detect and treat cancer will be moved from the bench to practical applications in patients. The OICR team is growing quickly. We are innovative, dedicated professionals who bring expertise to each of our roles. We are looking for individuals interested in being part of a culture of excellence that will result in Ontario being recognized internationally as a leading jurisdiction for cancer research.

Launched in December 2005, OICR is an independent institute funded by the Government of Ontario through the Ministry of Economic Development and Innovation.

For more information about OICR, please visit the website at www.oicr.on.ca.

POSTED DATE: February 15, 2013
CLOSING DATE: Posted until filled

Interested candidates may apply here
https://www.recruitingsite.com/csbsites/oicr/JobDescription.asp?JobNumbe…

OICR has a diverse workforce and is an equal opportunity employer.

The Ontario Institute for Cancer Research thanks all applicants. However, only those under consideration will be contacted.

Resume Format: If you elect to apply, you will need a text or HTML version of your resume so that you can cut and paste it into the application box provided. Before you submit the completed application, you will be asked to attach one or two files to your application. Please attach your resume as a .doc file.

Faculty position at University of Saskatchewan

admin — Wed, 20 Feb 2013 05:43:27 +0000

The College of Medicine invites applications for a five year term faculty position at the Assistant Professor level in the area of bioinformatics. The position will be affiliated with the Department of Biochemistry with a joint appointment in the Department of Computer Science in the College of Arts and Science.

The successful candidate will be expected to have a PhD with at least some formal education in bioinformatics, and a strong research background in the area. The candidate is expected to demonstrate the ability to establish an independent research program involving high throughput genome sequencing and sequence assembly, genome annotation, comparative genomics, transcriptomics using RNAseq, metagenomics, and proteins/protein interaction networks. The successful candidate is also expected to demonstrate the potential to apply their expertise in these areas of bioinformatics to develop collaborative research projects with research groups affiliated with the Colleges of Medicine and Arts and Science. Collaborative research opportunities are available through PRISM (Center for Proteomics Research in Interactions and Structure of Macromolecules) and other groups in the basic and health sciences at the University of Saskatchewan.

The candidate is expected to attract external research funding, and to lead a vigorous research program involving graduate students. The successful candidate will contribute to the academic programs of the departments through research and training including contributions to the Bioinformatics undergraduate program offered in the College of Arts and Science, and training in bioinformatics at the graduate level.

The University of Saskatchewan (www.usask.ca) is a research-intensive institution with 22,000 students and 7,000 faculty and staff, and a strong reputation for innovation and excellence. It is home to two of the largest science projects in the country – the Canadian Light Source synchrotron (www.lightsource.ca) and the Vaccine and Infectious Disease Organization / International Vaccine Centre (www.vido.org), as well as a University-related Research Park at Innovation Place (www.innovationplace.com). The beautiful U of S campus is located on the shores of South Saskatchewan River in Saskatoon, a city with a diverse and thriving economic base and vibrant cultural life (www.tourismsaskatoon.com).

Review of applications will begin on April 1, 2013 and continue until the position is filled. Preferred starting date is July 1, 2013. Please submit curriculum vita, a cover letter outlining research interests and experience, and the names of three referees, preferably electronically, to:
Dr Nicholas Ovsenek (email: lori.lisitza@usask.ca)
College of Medicine
University of Saskatchewan
Health Sciences Bldg, Box 2
107 Wiggins Road, Rm 2D01
Saskatoon, Saskatchewan S7N 5E5
Canada

The University of Saskatchewan is strongly committed to a diverse and inclusive workplace that empowers all employees to reach their full potential. All members of the university community share responsibility for developing and maintaining an environment in which differences are valued and inclusiveness is practiced. The university welcomes applications from those who will contribute to the diversity of our community. All qualified candidates are encouraged to apply; however, Canadian citizens and permanent residents will be given priority.

INB