True Life as a Continual “Student”

It’s a sign of a good attitude when you hear people say they’re perpetually a student of life. Academia is, unsurprisingly, one of the career tracks where you’re seemingly always learning something new for your job, and I think all of us are here because we love to learn. I’d venture a guess that science fields in particular garner a disproportionate number of INTJ (my Myers & Briggs type), and we like to get things as right as possible, even if that means deconstructing the current system and starting over. That’s certainly, for better of worse, who I am. It’s not good enough until it’s the best it can possibly be (and now you can see why I’m prone to perfectionism), and I relentlessly pursue the best solution to any problem. I generally see it as a strength (I guess that’s obvious because I do it), though others might see it as a hindrance, or at least a waste of time to “do something better” that works just fine as is. It has led me to learn a lot that I wouldn’t have otherwise learned. Plenty of what I’ve learned on my career track, though, is just necessity and not striving for the perfect solution. Thinking back to especially grad school and my current job, I wanted to look back at what I’ve learned when, and chronicle it here. It’s a mix of programming languages, operating systems, software/libraries, platforms and even fields of study with associated tools.

  • Before college: DOS, HTML, QBASIC, Visual Basic
  • ¬†Undergrad
    • 2004: MATLAB, Java
    • 2006: Linux, bash scripting, using servers
  • MS
    • 2009: SAS, ArcGIS
    • 2010: Patch analyst, FRAGSTATS
    • 2011: Sigma Plot, PC-Ord, R
  • PhD
    • 2012: remote sensing (ENVI), various landscape ecology tools (introduced to Conefor, etc. through class labs)
    • 2013: Python
    • 2014: GME
    • 2015: GDAL, CSS
  • postdoc
    • 2016: STELLA
    • 2017: NetCDF, Google Earth Engine, Github

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