I frequently wonder what the error bars on my life choices are.
I frequently wonder what the error bars on my life choices are.
One of the most distinctive parts of science, relative to other fields, is the practice of communicating findings through peer-reviewed journal publications.
In many applications, including cheminformatics, it’s common to have datasets that have too many dimensions to analyze conveniently.
This Easter week, I’ve been thinking about why new ventures are so important.
While scientific companies frequently publish their research in academic journals, it seems broadly true that publication is not incentivized for companies the same way it is for academic groups.
If you are a scientist, odds are you should be reading the literature more.
It’s a truth well-established that interdisciplinary research is good, and we all should be doing more of it (e.g.
Recently, I’ve been working to assign the relative configuration of some tricky diastereomers, which has led me to do a bit of a deep dive into the world of computational NMR prediction.
Python is an easy language to write, but it’s also very slow.
Eric Gilliam, whose work on the history of MIT I highlighted before, has a nice piece looking at Irving Langmuir’s time at the General Electric Research Laboratory and how applied science can lead to advances in basic research.
When thinking about science, I find it helpful to divide computations into two categories: models and oracles.