
Q3/Q4 Community Calls 2023
The primary goal for every meeting is exchange – what experience can you share with others that might open them up to a new way of thinking about and doing training?
A global community of practice for short-format training in the life sciences
Lifescitrainers.org is a way to connect anyone and everyone who does short-format training (workshops, boot camps, short-courses, etc.) in the life sciences. This site is a place to share resources, advice, and conversation – all in the service of improving our teaching and our careers.
In many areas of the life sciences new technologies and approaches (especially, but not only computational ones) are changing rapidly. It’s not possible for formal training (undergraduate/graduate) to keep pace, but short-format training can fill these gaps. Short-format training comes with its own set of challenges, and this community works together to address them.
Membership is open to all trainers who serve researchers and educators in the life sciences
Most of the community is active on Slack (online chat forum).
This site is new, but as we grow we will host member posts on training content and videos of online meetups and presentations. You can also join the trainer’s registry and/or post a biography.
The primary goal for every meeting is exchange – what experience can you share with others that might open them up to a new way of thinking about and doing training?
New web technologies like WebAssembly enable us to build more interactive tutorial environments in sandbox.bio.
Recently, LifeSciTrainers.org held two community calls to discuss the potential of using ChatGPT, a large-scale AI language model, as a tool for training and teaching bioinformatics.
Peer-to-peer training is essential in Academia, even when not recognized. We should not only recognize it, but design a structure to facilitate and support it.
What will it mean to teach and learn about bioinformatics with the assistance of AI?
Application of project-based learning in a training workshop provides an opportunity to explore methods and strategies that can be adapted to solve real-world data analysis problems.