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This guide by laboratory automation veteran Joe Liscouski takes an updated look at the state of implementing laboratory automation, with a strong emphasis on the importance of planning and management as early as possible. It also addresses the need for laboratory systems engineers (LSEs)—an update from laboratory automation engineers (LAEs)—and the institutional push required to develop educational opportunities for those LSEs. After looking at labs then and now, the author examines the transition to more automated labs, followed by seven detailed goals required for planning and managing that transition. He then closes by discussing LSEs and their education, concluding finally that "laboratory technology challenges can be addressed through planning activities using a series of goals," and that the lab of the future will implement those goals as early as possible, with the help of well-qualified LSEs fluent in both laboratory science and IT.
This is an advanced University of Adelaide-created course that is released on the edX platform, and is part of a university MicroMasters Program. The scheduled 10-week course is designed to help learners to better "apply computational thinking in data science" using tools such as "mathematical representations, probabilistic and statistical models, dimension reduction and Bayesian models." The course is free; a certificate of completion costs $249. The course requires on average eight to 10 hours a week of effort. Access to the class is on-demand.
