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Nils Norlin @nilsnorlin.bsky.social · 17/09/2026

I am looking for postdoc candidates for two opportunities in my lab at Lund University. 1. Co-application for a two-year postdoc scholarship on method development in 3D spatial biology, with applications in lung physiology, cancer and neuroscience.

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Nils Norlin @nilsnorlin.bsky.social · 08/01/2026

Excited to share our new paper on the future of autonomous scientific laboratory work (together with @henrypinkard.bsky.social ). Perhaps the path to intelligent scientific instruments starts with rethinking what data we save ? www.nature.com/articles/s41... rdcu.be/eW7SU

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Reposted by Nils Norlin

Lucien Hinderling @lhinderling.bsky.social · 01/10/2025

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...

screenshots of some of the sample implementations

Screenshot of smartmicroscopy.github.io/implementations.html, showing an overview of collected implementation examples

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Reposted by Nils Norlin

Nature Methods @natmethods.nature.com · 17/09/2025

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...

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Reposted by Nils Norlin

The BioImage Archive @bioimagearchive.bsky.social · 15/09/2025

🎉 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

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Reposted by Nils Norlin

Lucien Hinderling @lhinderling.bsky.social · 21/08/2025

🔬🧠 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:

Figure legend: Categories and capabilities of smart microscopy systems integrating real-time image analysis and feedback control. Top: Smart microscopy workflows can be classified based on the driving logic behind decision-making: Event-driven (reacting to rare biological events), Outcome-driven (using feedback-control to steer biological systems toward a desired state), Quality-driven (optimizing signal quality or imaging metrics), and Information-driven (guided by models that predict which measurements/perturbations will yield the most informative data). Middle: Central feedback loop between the microscope and an image analysis system, which continuously
exchanges images and commands to guide acquisition dynamically. Bottom: Key control actions enabled by smart microscopy: adjusting imaging modality (e.g. switching from brightfield to fluorescence, adjusting sampling rate), repositioning the field of view (e.g. tracking, drift correction), optimizing acquisition settings (e.g. adaptive optics),
and performing photomanipulation (e.g. FRAP, ablation, optogenetics).

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Nils Norlin @nilsnorlin.bsky.social · 11/09/2025

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.

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