There is an exciting postdoc opportunity for folks interested in quantitative approaches to studying evolution in Michael Gilchrist’s lab at the University of Tennessee. I knew Mike when we were both in New Mexico. He’s really sharp, a nice guy, and a very patient teacher. He taught me all about likelihood and numerical maximization and opened my mind to a whole new way of modeling biological systems. This will definitely be a great postdoc for the right person, especially since NIMBioS is at UTK as well. Here’s the ad:
Outstanding, motivated candidates are being sought for a post-doctoral position in the Gilchrist lab in the Department of Ecology & Evolutionary Biology at the University of Tennessee, Knoxville. The successful candidate will be supported by a three year NSF grant whose goal is to develop, integrate and test mathematical models of protein translation and sequence evolution using available genomic sequence and expression level datasets. Publications directly related to this work include Gilchrist. M.A. 2007, Molec. Bio. & Evol. (http://www.tinyurl/shahgilchrist11) and Shah, P. and M.A. Gilchrist 2011, PNAS (http://www.tinyurl/gilchrist07a).
The emphasis of the laboratory is focused on using biologically motivated models to analyze complex, heterogeneous datasets to answer biologically motivated questions. The research associated with this position draws upon a wide range of scientiﬁc disciplines including: cellular biology, evolutionary theory, statistical physics, protein folding, diﬀerential equations, and probability. Consequently, the ideal candidate would have a Ph.D. in either biology, mathematics, physics, computer science, engineering, or statistics with a background and interest in at least one of the other areas.
The researcher will collaborate closely with the PIs (Drs. Michael Gilchrist and Russell Zaretzki) on this project but potentiall have time to collaborate on other research projects with the PIs. In addition, the researcher will have opportunties to interact with other faculty members in the Division of Biology as well as researchers at the National Institute for Mathematical and Biological Synthesis (http://www.nimbios.org).
Review of applications begins immediately and will continue until the position is filled. To apply, please submit curriculum vitae including three references, a brief statement of research background and interests, and 1-3 relevant manuscripts to mikeg[at]utk[dot]edu.
Some time ago in academia we realized that it didn’t make sense for individual scientists or even entire departments to maintain their own high performance computing resources. Use of these resources by an individual is intensive, but sporadic, and maintenance of the resources is expensive  so the universities soon realized they were better off having centralized high performance computing centers so that computing resources were available when needed and the averaging effects of having large numbers of individuals using the same computers meant that the machines didn’t spend much time sitting idle. This was obviously a smart decision.
So, why haven’t universities been smart enough to centralize an even more valuable computational resource, their computer labs?
As any student of Software Carpentry will tell you, it is far more important to be able to program well than it is to have access to a really large high performance computing center. This means that the most important computational resource a university has is the classes that teach their students how to program, and the computer labs on which they rely.
At my university  all of the computer labs on campus are controlled by either individual departments or individual colleges. This means that if you want to teach a class in one of them you can’t request it as a room through the normal scheduling process, you have to ask the cognizant university fiefdom for permission. This wouldn’t be a huge issue, except that in my experience the answer is typically a resounding no. And it’s not a “no, where really sorry but the classroom is booked solid with our own classes,” it’s “no, that computer lab is ours, good luck” .
And this means that we end up wasting a lot of expensive university resources. For example, last year I taught in a computer lab “owned” by another college . I taught in the second class slot of a four slot afternoon. In the slot before my class there was a class that used the room about four times during the semester (out of 48 class periods). There were no classes in the other two afternoon slots . That means that classes were being taught in the lab only 27% of the time or 2% of the time if I hadn’t been granted an exception to use the lab .
Since computing skills are increasingly critical to many areas of science (and everything else for that matter) this territoriality with respect to computer labs means that they proliferate across campus. The departments/colleges of Computer Science, Engineering, Social Sciences, Natural Resources and Biology  all end up creating and maintaining their own computer labs, and those labs end up sitting empty (or being used by students to send email) most of the time. This is horrifyingly inefficient in an era where funds for higher education are increasingly hard to come by and where technology turns over at an ever increasing rate. Which  brings me to the title of this post. The solution to this problem is for universities to stop allowing computer labs to be controlled by individual colleges/departments in exactly the same way that most classrooms are not controlled by colleges/departments. Most universities have a central unit that schedules classrooms and classes are fit into the available spaces. There is of course a highly justified bias to putting classes in the buildings of the cognizant department, but large classes in particular may very well not be in the department’s building. It works this way because if it didn’t then the university would be wasting huge amounts of space having one or more lecture halls in every department, even if they were only needed a few hours a week. The same issue applies to computer labs, only they are also packed full of expensive electronics. So please universities, for the love of all that is good and right and simply fiscally sound in the world, start treating computer labs like what they are: really valuable and expensive classrooms.
 Think of a single scientist who keeps 10 expensive computers, only uses them a total of 1-2 months per year, but when he does the 10 computers aren’t really enough so he has to wait a long time to finish the analysis.
 And I think the point I’m about to make is generally true; at least it has been at several other universities I’ve worked over the years.
 Or in some cases something more like “Frak you. You fraking biologists have no fraking right to teach anyone a fraking thing about fraking computers.” Needless to say, the individual in question wasn’t actually saying frak, but this is a family blog.
 As a result of a personal favor done for one administrator by another administrator.
 I know because I took advantage of this to hold my office hours in the computer lab following class.
 To be fair it should be noted that this and other computer labs are often used by students for doing homework (along with other less educationally oriented activities) when classes are not using the rooms, but in this case the classroom was a small part of a much larger lab and since I never witnessed the non-classroom portion of the lab being filled to capacity, the argument stands.
 etc., etc., etc.
There is a new postdoctoral research position available in Jim Brown’s lab at the University of New Mexico to study some of the major patterns of biodiversity. We know a bit about the research and it’s going to be an awesome project with a bunch of incredibly bright people involved. Jim’s lab is also one of the most intellectually stimulating and supportive environments that you could possibly work in. Seriously, if you are even remotely qualified then you should apply for this position. We’re both thinking about applying and we already have faculty positions🙂. Here’s the full ad:
The Department of Biology at the University of New Mexico is seeking applications for a post-doc position in ecology/biodiversity. The post doc will be expected to play a major role in a multi-investigator, multi- institutional project supported by a four-year NSF Macrosystems Ecology grant. The research will focus on metabolic processes underlying the major patterns of biodiversity, especially in pervasive temperature dependence and requires a demonstrated working knowledge of theory, mathematical and computer
Applicants must have a Ph.D. in ecology or a related discipline.
Review begins with the first applications and continues until the position is filled. Applicants must submit a cover letter and a curriculum vitae along with at least three phone numbers of references, three letters of recommendation and PDF’s of relevant preprints and publications to be sent directly to firstname.lastname@example.org attn: James Brown. Application materials must be received by July 25, 2011, for best consideration.
Questions related to this posting may be directed to Dr. James Brown at email@example.com or to Katherine Thannisch at firstname.lastname@example.org.
The University of New Mexico is an Equal Opportunity/Affirmative Action Employer and Educator. Women and underrepresented minorities are encouraged to apply.
There is an excellent post on open science, prestige economies, and the social web over at Marciovm’s posterous*. For those of you who aren’t insanely nerdy** GitHub is… well… let’s just call it a very impressive collaborative tool for developing and sharing software***. But don’t worry, you don’t need to spend your days tied to a computer or have any interest in writing your own software to enjoy gems like:
Evangelists for Open Science should focus on promoting new, post-publication prestige metrics that will properly incentivize scientists to focus on the utility of their work, which will allow them to start worrying less about publishing in the right journals.
*A blog I’d never heard of before, but I subscribed to it’s RSS feed before I’d even finished the entire post.
**As far as biologists go. And, yes, when I say “insanely nerdy” I do mean it as a complement.
Advertisements for three exciting postdoctoral positions came out in the last week.
Interface between ecology, evolution and mathematics
The first is with Hélène Morlon’s group in Paris. Hélène and I were postdocs in Jessica Green’s lab at the same time. She is both very smart and extremely nice, oh, and did I mention, her lab is in PARIS. Here’s the ad. If it’s a good fit then you couldn’t go wrong with this postdoc.
A postdoctoral position is available in my new lab at the Ecole Polytechnique and/or at the Museum of Natural History in Paris to work at the interface between ecology-evolution and mathematics. Candidates with a background in biology and a strong interest in modeling, or with a theoretical background and a strong interest in biology, are encouraged to apply. More information is available here. Potential candidates should feel free to contact me. The deadline for application is May 8th.
The other two postdocs are associated with Tim Keitt’s lab (which I consider to be one of the top quantitative ecology groups out there).
Mechanistic niche modeling and climate change impacts
A postdoctoral position is anticipated as part of a collaborative project to develop and evaluate mechanistic niche models that incorporate geographic variation in physiological traits. The post doc will be based in Michael Angilletta’s laboratory at Arizona State University, but will interact with members of Lauren Buckley’s lab at the University of North Carolina in Chapel Hill and Tim Keitt’s lab at the University of Texas in Austin. The post doc will be expected to engage in modeling activities and coordinate lab studies of thermal physiology. Experience with mathematical modeling in C++, MATLAB, Python or R is beneficial and familiarity with environmental data and biophysical ecology is beneficial. More here.
Ecological forecasting or statistical landscape genetics
The Keitt Lab at the University of Texas at Austin seeks a postdoctoral investigator to join an interdisciplinary NSF-funded project linking ecophysiology, genomics and climate change. The position requires excellent modeling skills and the ability to engage in multidisciplinary research. Research areas of interest include either ecological forecasting or statistical landscape genomics. More here.
So, if you’re looking for a job go check out these great opportunities.
An increasingly large number of folks doing research in ecology and other biological disciplines spend a substantial portion of their time writing computer programs to analyze data and simulate the outcomes of biological models. However, most ecologists have little formal training in software development¹. A recent survey suggests that we are not only; with 96% of scientists reporting that they are mostly self-taught when it comes to writing code. This makes sense because there are only so many hours in the day, and scientists are typically more interested in answering important questions in their field than in sitting through a bachelors degree worth of computer science classes. But, it also means that we spend longer than necessary writing our software, it contains more bugs, and it is less useful to other scientists than it could be².
Software Carpentry to the Rescue
Fortunately you don’t need to go back college and get another degree to substantially improve your knowledge and abilities when it comes to scientific programming, because with a few weeks of hard work Software Carpentry will whip you into shape. Software Carpentry was started back in 1997 to teach scientists “the concepts, skills, and tools they need to use and build software more productively” and it does a great job. The newest version of the course is composed of a combination of video lectures and exercises, and provides quick and to the point information on such critical things as:
along with lots of treatment of best practices for writing code that is clear and easy to read both for other people and for yourself a year from now when you sit down and try to figure out exactly what you did³.
The great thing about Software Carpentry is that it skips over all of the theory and detail that you’d get when taking the relevant courses in computer science and gets straight to crux – how to use the available tools most effectively to conduct scientific research. This means that in about 40 hours of lecture and 100-200 hours of practice you can be a much, much, better programmer who rights code more quickly, with fewer bugs, that be easily reused. I think of it as boot camp for scientific software development. You won’t be an expert marksman or a black belt in Jiu-Jitsu when you’re finished, but you will know how to fire a gun and throw a punch.
I can say without hesitation that taking this course is one of the most important things I’ve done in terms of tool development in my entire scientific career. If you are going to write more than 100 lines of code per year for your research then you need to either take this course or find someone to offer something equivalent at your university. Watch the lectures, do the exercises, and it will save you time and energy on programming; giving you more of both to dedicate to asking and answering important scientific questions.
¹I took 3 computer science courses in college and I get the impression that that is about 2-3 more courses than most ecologists have taken.
²I don’t know of any data on this, but my impression is that over 90% of code written by ecologists is written by a single individual and never read or used by anyone else. This is in part because we have no culture of writing code in such a way that other people can understand what we’ve done and therefore modify it for their own use.
³I know that I’ve decided that it was easier to “just start from scratch” rather than reusing my own code on more than one occasion. That won’t be happening to me again thanks to Software Carpentry
If you use R (and it seems like everybody does these days) then you should check out RStudio – an easy to install, cross-platform IDE for R. Basically it’s a seamless integration of all of the aspects of R (including scripts, the console, figures, help, etc.) into a single easy to use package. For those of you are familiar with Matlab, it’s a very similar interface. It’s not a full blown IDE yet (no debugger; no lint) but what this actually means is that it’s simple and easy to use. If you use R I can’t imagine that you won’t love this new (and open source!) tool.