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DATES: July 2-6, 2012
LOCALE: Huxley Building, Imperial College London
URL: http://cc.doc.ic.ac.uk/asc12
There are great challenges in the development of scientific computation: data sets are growing exponentially, models are becoming increasingly complex, while many of the latest machines are getting more costly and harder to program.
This Summer School will provide an introduction to a new dataflow approach for accelerating computation, which has recently been proven commercially. This approach involves compiling dataflow programs into special-purpose compute engines targeting advanced reconfigurable hardware. It has been used in many scientific computations, including those in geophysics, bioinformatics, and quantum chemistry. Promising results are reported.
The Summer School will consist of talks given by leading experts from academia and from industry. There will be practicals to enable attendants to have hands-on experience of developing solutions using this approach. Attendants are invited to bring some of their problems, which can be used as case studies to illustrate the development and optimisation of designs.
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BACKGROUND:
The laboratories of Profs Jun S. Liu and X. Shirley Liu invite applications for a joint postdoctoral position. Jun Liu ([link]) is at the Statistics Department at Harvard University and his research focuses on Bayesian modeling and computation methodology, statistical genetics, and Monte Carlo methods, with applications to large-scale computation and optimization. Shirley Liu (http://liulab.dfci.harvard.edu/) is at the Department of Biostatistics and Computational Biology at Dana-Farber Cancer Institute and Harvard School of Public Health, and her research focuses on genomics and bioinformatics of transcription and epigenetic gene regulation, with applications to cancer biology. The postdoctoral fellow will be jointly supervised by both laboratories to work on statistical and computational methodologies for gene regulation problems.
REQUIREMENTS:
Ideal applicant should have:
* PhD degree in physical sciences or related fields
* Strong programming skills: ((Python | Perl) & (C | C++ | Java) & R)
* Strong quantitative background (machine learning, Bayesian inference, etc.) or computational genomics experiences (DNA sequence analysis, microarray analysis, etc.)
* Good knowledge of molecular biology and genomics
* At least two (four if co-first author) first author papers written in English in previous area of research (not necessarily computational biology) with submitted, accepted or published status in journals or conference proceedings
* Good spoken and written communication skills, mature and motivated.
* In addition, applicant must be able to visit Boston for potential interviews without visa application.
HOW TO APPLY:
Interested applicants should submit a letter of interest with a research proposal for a project (~2 pages) to be conducted during postdoctoral training, CV, and three references (including name and contact information) to jliu (At) stat (Dot) harvard (Dot) edu and xsliu (At) jimmy (Dot) harvard (Dot) edu and with subject line "Joint postdoc application".
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BACKGROUND:
The laboratory of X. Shirley Liu (http://liulab.dfci.harvard.edu/) invites applications for a postdoctoral position at the Department of Biostatistics and Computational Biology at Dana-Farber Cancer Institute and Harvard School of Public Health. Research in the Liu Lab focuses on genomics and bioinformatics of transcription and epigenetic gene regulation, with applications to cancer biology. Her laboratory developed a number of widely used algorithms for transcription factor motif finding (cited over 1500 times), ChIP-chip/seq and DNase-seq data analysis (over 6000 users). Shirley Liu published 92 papers, with 27 in Nature, Science or Cell series. She has good track record for mentoring, with one PhD student and five postdocs graduated from her lab taking on tenure track faculty positions (since she became a faculty in 2003).
REQUIREMENTS:
Ideal applicant should have:
* PhD degree in physical sciences or related fields
* Strong programming skills: ((Python | Perl) & (C | C++ | Java) & R)
* Strong quantitative background (machine learning, Bayesian inference, etc.) or computational genomics experiences (DNA sequence analysis, microarray analysis, etc.)
* Good knowledge of molecular biology and genomics
* At least two (four if co-first author) first author papers written in English in previous area of research with submitted, accepted or published status in journals or conference proceedings
* Good spoken and written communication skills, mature and motivated.
* In addition, applicant must be able to visit Boston for potential interviews without visa application.
HOW TO APPLY:
Interested applicants should submit a letter of interest with a research proposal for a project (~2 pages) to be conducted during the postdoctoral training, CV, and three references (including name and contact information) to xsliu (At) jimmy (Dot) harvard (Dot) edu and with subject line "Postdoc application".
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We are releasing e-Bio, which provides e-learning materials such as lectures, tutorials, demos and experimental protocols in bioscience. This is an extension of the annual virtual training workshop on bioinformatics, which was held 5 times since 2006.
Because of increasing demand for e-learning, we have decided to expand the scope of the workshop: to expand the field to bioscience; to expand the category of e-learning materials including not only lectures but also tutorials, demos and experimental protocols etc.; and to extend the availability of some e-learning materials not only limited to the annual workshops but also open all the year round.
The e-Bio system is capable of holding multiple workshops at the same time. We plan to have various training workshops on specific topics, tutorial sessions along with the ordinary conferences, and the webcasting of conference sessions.
AVAILABILITY:
e-Bio can be accessed at: http://www.abren.net/e-bio/
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DATES: September 20-21, 2012
LOCALE: Varna, Bulgaria
URL: http://biocomp.bio.uni-plovdiv.bg/
Topics of interest include, but are not limited to: High-performance bio-computing; High-throughput sequencing data analysis (NGS); Bio-ontologies; Molecular evolution; Comparative genomics; Molecular modeling and simulation; Computational genetics; Computational proteomics; Data mining and visualization; Software tools and applications; Gene expression analysis; Gene networks; Structural biology; Genome analysis; Databases; Systems biology. Special topic: bioinformatics and miRNAs.
Recent achievements in these fields will be presented. The conference will include plenary and poster sessions. Participant's proposals will be taken under advisement in compiling the program.
IMPORTANT DATES:
Abstract Submission Deadline: August 20, 2012
Early Registration Fee Payment Deadline August 20, 2012
Arriving, Poster set up, Registration: September 19, 2012
Plenary and Poster Sessions: September 20-21, 2012
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