Most scientific instruments throw away exactly the data AI would need to learn how to operate them. In @natmethods.nature.com this month, @nilsnorlin.bsky.social and I describe in how capturing this data could let us train AI to run experiments like expert scientists. doi.org/10.1038/s415...

Want to get started with smart microscopy? 🧠🔬 Check out our online repository with implementations from labs and industry -- lots of practical tips and links to sample code! smartmicroscopy.github.io/implementati... More details in the ✨updated preprint!✨ www.biorxiv.org/content/10.1...

A new Perspective discusses the challenges of sharing annotated image datasets and offers advice for improving bioimage annotation and reuse, particularly for AI applications. www.nature.com/articles/s41...

🎉 Our paper “MIFA: Metadata, Incentives, Formats and Accessibility guidelines to improve the reuse of AI datasets for bioimage analysis” is out in @natmethods.nature.com! Community-driven standards to make bioimage data AI-ready & reusable. 👉 www.nature.com/articles/s41... #AI #Bioimaging #FAIRdata

🔬🧠 Our paper on smart microscopy & the issue of interoperability! www.biorxiv.org/content/10.1... LONG THREAD WARNING: Smart microscopy uses real-time image analysis to automatically guide the acquisition or perturbation of the sample (closed feedback-control loop). Many applications exist:

Norlin Lab is expanding! Postdoctoral scholarship available: Computational microscopy with applications in lensless imaging. Preferably, you have already developed applications using ML/AI in microscopy, though this is not strictly required.