What follows is an assortment of things that I thought would be useful to other people. Most are things that I use, or have used, and that have been particularly helpful, along a few items that we have developed in our lab group.
Graduate studies and academic careers
- Scott Keogh's page with Lots of Advice for Graduate Students. In particular, I found the comments by Stearns and Huey useful when I was a student.
- Results of a
survey (2009) of newly hired professors at academic
institutions, with statistics on their academic qualifications.
Jonathon C. Marshall, Paul Buttars, Thomas Callahan, John J. Dennehy, D. James Harris, Bryce Lunt, Markus Mika, Robert Shupe. 2009. In the Academic Job Market, will You be Competitive? A Case Study in Ecology and Evolutionary Biology. Israel Journal of Ecology and Evolution 55: 381-392.
- Re-envisioning the Ph.D. -- A collection of materials and resources pertaining to graduate education. The name of the site refers to Ph.D. students, but there is material that applies to graduate education in general.
- Computing resources at the University of Wyoming
- Linux--an open-source operating system. Various vendors package the base system with powerful tools that give you full use and control of your computer. Linux is available for a large number of computer architectures (on CD from vendors, or for free online). These days I use it on Intel-compatible systems (e.g., Fedora, CentOS).
- For additional UNIX tools on Mac OS X, I use the packages provided by the FINK project.
- Perl (Practical Extraction and Report Language)--a programming language that is an invaluable tool for working with datasets, extracting data from text files, or writing interactive web pages. A set of perl tools specific to biology is available from BioPerl.
- For choosing colors for on-screen presentations and manuscripts, ColorBrewer provides some valuable guidance. It's not just for maps. There is also an implementation of this for R (package RColorBrewer).
- My PGP public key is available (CBE4A912).
- R--A language and environment for statistical computing and excellent graphics. R provides a wide variety of statistical and graphical techniques (linear and nonlinear modeling, statistical tests, time series analysis, classification, clustering, etc.). R is available at no cost for Windows, Mac OS, linux and various forms of Unix.
- GSL--The GNU Scientific Library A library of mathematical functions for C-programmers. Includes lots of essential things: good random number generators, memory allocation routines, statistics etc.