NESCent Short Courses - Request for Proposals
NESCent welcomes ideas and proposals for short courses (1-2 weeks) at the postgraduate level on topics of relevance to synthetic evolutionary science.
(NESCent also provides co-sponsorship for existing short courses on evolutionary topics. Click here for more information on this.)
Requests for proposals are solicited in two phases.
Phase 1. Solicitation of Course Ideas from the Evolution Community
This phase has recently been completed (June, 2010) and the five topics that received the most community support are listed below.
Phase 2. Solicitation of Full Proposals for Short Courses
While the five topics listed below are of particular interest to NESCent (based on community voting) anyone is welcome to submit a full proposal to deliver a course on any evolutionary topic as part of Phase 2.
Proposals should include the following components:
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Course Title
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Course Instructor(s) - Include full name and contact information for all instructors. CVs should be provided as supporting material, and relevant teaching experience should be emphasized.
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Course Description (<1 page), including:
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The importance of the topic to synthetic evolutionary science.
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The intended audience (typically, but not exclusively, postgraduate researchers and educators in evolutionary biology and informatics).
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Evidence for unmet need and demand within the evolutionary research, informatics and/or education communities.
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Syllabus (<1 page) – A breakdown of the proposed topics, instructor contributions, and class activities.
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IT needs (1-3 paragraphs), such as specialized software or intensive computing requirements. Note that NESCent courses are expected to make all learning materials available during the course online in tutorial format, and NESCent provides a course wiki for this purpose.
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Short instructor biographies (1 paragraph each, describing qualifications). In addition, please include a two-page CV for each instructor with an emphasis on relevant teaching experience.
Proposal Submission
Proposals will be accepted in digital format only as a single PDF file. Graphics should be embedded directly into the proposal document. Note that proposals should be submitted as a single pdf file including all of the components listed above. Proposals are submitted electronically. Please login first if you have already created a profile. Proposals should be submitted by July 10th, 2010.
Review Criteria
The NESCent Advisory Board will review the full course proposals. Review criteria include:
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The relevance of the course to NESCent’s goal of promoting synthetic evolutionary science.
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Evidence for course demand. (Please note: All proposals will be evaluated on their own merit. However, full proposals for courses which have not been vetted via Phase I should pay particular attention to providing ample evidence/justification for course demand.)
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The uniqueness of the course relative to offerings available elsewhere.
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The qualifications and the diversity of the instructors.
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The extent to which the course employs active, hands-on learning on the part of the students, and engages the students by using real examples and data.
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For informatics courses, the extent to which the course promotes the adoption and collaborative development of open source and platform-independent software tools.
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The extent to which the course will reach a diverse audience of students, including under-represented groups. NESCent is particularly interested in promoting the participation of women in informatics.
Budget
NESCent will be responsible for the course budget. Student registration is generally kept below $400, depending on the duration and number of instructors, and does not include housing and travel. Instructors will receive an honorarium of $100/day ($50/day for co-instructors and teaching assistants), in addition to travel, housing and per diem expenses. First-time course organizers collectively receive an additional honorarium of $500.
Logistical information
Courses are generally 7-10 days in duration and offered on-site at NESCent during the summer break; however, other arrangements can be considered. Courses are expected to have at least 12 and no more than 24 students. Courses will be scheduled after acceptance, based on instructor and facility availability.
NESCent will handle the following arrangements:
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Distributing the course announcement (with content provided by instructors)
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Hosting the course website and wiki (with content provided by instructors) and general IT/network support
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Receipt of student applications (instructors will review the applications once received)
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Notification of student application outcomes.
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Making travel awards to individuals from under-represented groups.
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Student registration
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Housing and ground transportation for instructors and students
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Ground transportation for students/instructors
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Catering at NESCent
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Travel arrangements for instructors
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VISA arrangements for international visitors
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Extracurricular events and activities (group meals, other social events)
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Finances
The five ideas generated from Phase I are listed below.
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Idea #1 - Practical Computing for Biologists
This course would cover some of the simple but powerful skills that all scientists should know, in a world of increasingly complex analyses. The specific sections include working with text files, command-line operations, python programming, working with graphics files, and more. The target audience would be grad students, post-docs, technicians, and faculty.
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Idea #2 - Defining and Implementing Likelihood Models for Comparative and Diversification Studies
Recent developments in organizing and analyzing phylogenetic data have facilitated the reconstruction of very taxon-rich phylogenies. When combined with information about organismal features and biodiversity, such large phylogenies have the potential to answer detailed questions about evolutionary processes.
Several types of comparative and diversification analyses can be carried out with stand-alone programs or R packages. Unfortunately, these programs are often black boxes to the average user and in many cases one wants to test more complex evolutionary hypotheses than those that are available or implement ones own ideas about the evolutionary process. The goal of this course is to get from a conceptual idea of how evolution works to the code that implements the concept in a likelihood framework and optimizes the model.
Specific topics could include defining and implementing diversification models, models of continuous and discrete character change, models describing the evolution of multidimensional features, Markov-modulated models, and estimating ancestral states for such models. The intended audience is one of evolutionary biologists with an interest in understanding the statistical and computational aspects of comparative and diversification analysis.
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Idea #3 - Testing Evolutionary Hypotheses. Maximum Likelihood and Bayesian Approaches
Maximum likelihood and Bayesian approaches are statistical tools frequently used in Evolutionary Biology. The statistical comparison of posterior probabilities or ML results changed the framework to post and test hypothesis in evolution. Many different statistical models are currently used in evolutionary biology. They are frequently used to test for the best model of sequence evolution, phylogeny and ancestral character reconstruction, recombination, dates and rates of divergence, coevolution, molecular adaptation in comparative and population genomics, etc. Many program packages such as Beast, MrBayes, PAML, HyPhy and R environment are commonly used to test evolutionary hypotheses. The audience demanding this kind of knowledge range form PhD student to PI researchers, all looking to widening teir horizons of research. The necessity to test hypotheses in evolution is unavoidable, Hands-on training courses are required to acquire independent skills in the use of a diversity of tools and resources.
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Idea #4 - Next-gen Sequencing: Data Acquisition, Comparative Genomics, Design and Analysis for Population Genetics, Systematics and Development
Such a course would cover genome assembly and comparison, transcriptomics for differential mRNA expression, population genomic analyses, identification of homologs for systematics, and detection of cis-regulatory elements. Organization, storage and dissemination of data would also be covered.
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Idea #5 – Workshop on Evolutionary Quantitative Genetics
We propose a course on quantitative genetics that reviews the basics of its theory and emphasizes its connections to evolution at various time scales. Quantitative genetic theory for natural populations was developed considerably in the period 1970-90 and up to the present time. Textbooks have not kept pace with these developments, and currently few universities offer courses in this subject aimed at evolutionary biologists. At the same time, the greater ability to collect large amounts of data by computer, the development of statistical methods to analyze phenotypic evolution on phylogenies and in time series, and the realization that quantitative traits will not soon be fully explained by QTL analyses, have all pointed to the need for evolutionary biologists to understand evolutionary quantitative genetics.
The course will cover
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The basics of quantitative genetics theory and statistical methods
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Theory for maintenance and evolution of genetic variation in natural populations
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Mathematical models for change of quantitative characters on phylogenies
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Inference of evolutionary process from evolutionary patterns
The intended audience will be graduate students, postdocs, and junior faculty members in evolutionary biology. The course will introduce the theory and methods, and will also bring students in contact with leading investigators who have developed methods in evolutionary quantitative genetics.
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