HELLO FRIENDS! It has been a long, tough year since Rachel and I have posted here on Sweet Tea, Science. We’ve tried to keep up with people via Twitter (Mer’s, Rach’s, and the STS accounts) and Instagram (again we all have one!) but we started feeling that blogging itch once more, so we’re back. We wanted to start with updates on our academic and personal lives, because this blog is about the science journeys of two actual living people. We’ve had some highs and lows. Some heart-breaking tragedies and some magical love-filled unions.
This time last year I was enjoying the perks of summer in Colorado while exploring the in’s and out’s of working in an industry setting. I’ve had many summer adventures/internships/travels, but any work I’ve done has been 100% within the realm of academia. However, via a connection made through my advisor at the big statistics conference (Joint Statistical Meeting or JSM), I landed an internship at an environmental consulting agency. The further along I get in my studies the more certain I am I’d like to explore career options outside of academia; so this was an amazing opportunity.
I worked with Neptune & Co., a small but growing environmental consulting company focusing on environmental decision making though quality assurance, data science, and risk assessment. As an intern, I helped the other statisticians working on a project modelling the future (millions of years future!) risks and impacts of nuclear waste storage around the US. I loved being able to learn about an important issue from experts in various fields while applying what I’ve been learning over the past few years in my PhD studies.
We focused on the biotic impact portion of the models and worked to use what precious few data are available to create some distributions for variable such as: plant root shape,root depth, burrow depths, etc. All of these factors can potentially bring up buried contaminants if the burrows or roots venture too deep. It’s important to represent these as distributions (e.g. a Normal distribution LINK) rather than a point estimate (e.g. a mean or median) because it allows for more representation of uncertainty in the model.
Also we did lots of hiking and took adorable photos! Continue reading “Catching Up with STS – Meridith Edition”