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Lab work is most efficient when data can be acquired in an automated way. Especially when taking measurements over long durations automated acquisition avoids introducing human error and allows researchers to concentrate on the fun part of experimental work.

Open source software in easy to learn languages such as Python provides just as much, or more features/interoperability for lab automation than alternative commercial software.

In this hackathon, several researchers with 10+ years experience of lab automation will show you the power of using Python to quickly get a lab experiment running and display the measurements in a browser.

We will learn from companies that work in photonics and how they take advantage of Python to create easy interfaces to their software and hardware. Bring a laptop to participate in the exercise. There will also be plenty of time for mingling and discussion.