Jan Funke

We opened 4 PhD positions at @humantechnopole.bsky.social together with Polimi (see 👇).

My lab offers a PhD project on "Computational Morphogenesis": use state-of-the-art machine learning methods together with realistic simulations to build digital twins of developing tissue.

Apply by March 26.

Accelerating Innovation in Biology HHMI’s $500 million over the next 10 years will support AI-driven projects and embed AI systems throughout the scientific process in labs across HHMI.

Join us in building foundational datasets and models for microscopy with @jakobtroidl.bsky.social and many others

AI Engineer Pre-Training: lnkd.in/eyEEV5nm
AI Engineer Post-Training: lnkd.in/eShVQ3y9
Data Engineer Data: lnkd.in/eCvm58xH
Data Engineer Pipelines: lnkd.in/ec6qGJkX

ai.hhmi.org

Last call! This is a great opportunity for those interested in learning and applying SOTA ML/DL models to microscopy data with the leading experts in the field.

Personally super excited to be a lead TA along with the amazing @afoix.bsky.social and @edhirata.bsky.social!

Hope to see you there :)

Thanks Damian! I really appreciate your help in navigating the complexities of an international move. Can't wait to hang and work with you!

Thanks Anirban! Can't wait to see you all soon! :)

Research - Human Technopole Human Technopole’s research is based on a mix of fundamental and translational research. We will host extensive core expertise in basic research in areas relevant for the understanding of human biolog...

🎉 In January, I will join the new "Multimodal AI Across Scales" research area at the @humantechnopole.bsky.social in Milan 🎉

More soon, but for now: my lab and the new area will have postdoc, RSE, and PhD positions available.

Feel free to reach out if interested!

humantechnopole.it/en/research/

Today I departed from @hhmijanelia.bsky.social knowing that the next time I come here, I will be a visitor.

Thank you all for having me. I will miss you a lot.

This course is organized by @computingnature.bsky.social, @mattersoflight.bsky.social, and @janfunkey.bsky.social; together with an excellent team of TAs lead by @afoix.bsky.social, @edhirata.bsky.social, and @albertdm.bsky.social.

Reach out to any of us if you have questions about the course! :)

We moved the AI@MBL course "Deep Learning for Microscopy Image Analysis" to HHMI Janelia (@hhmijanelia.bsky.social).

Join us for two weeks of intense lectures, exercise, and hands-on project work!

Course dates: June 4-18 2026
Application by: January 15 2026

www.janelia.org/you-janelia/...

What an incredible trackathon! After two weeks of intense discussions and happy coding (and a lot of groundwork beforehand by @msschwartz21.bsky.social and Caroline Malin-Mayor), this lovely community emerged with a Graph Exchange File Format that is ready to use! Congrats, everyone! 🎉

E11 Bio is excited to unveil PRISM technology for mapping brain wiring with simple light microscopes. Today, brain mapping in humans and other mammals is bottlenecked by accurate neuron tracing. PRISM uses molecular ID codes and AI to help neurons trace themselves.

Read more: e11.bio/blog/prism

AI@MBL: Machine Learning for Microscopy Image Analysis | Marine Biological Laboratory The goal of this course is to familiarize researchers in the life sciences with state-of-the-art deep learning techniques for microscopy image analysis and to introduce them to tools and frameworks th...

We are looking forward to receiving your applications by April 30. Feel free to reach out to any of us with questions you might have!

www.mbl.edu/education/ad...

We have generous support from @hhmi.org and @cziscience.bsky.social to provide financial aid. If you have doubts that your institution can pay for you, apply anyway and indicate that you seek financial aid.

If you get selected (admission is need blind), we'll be working with you to find a solution.

...
* Jan Funke @janfunkey.bsky.social
* Martin Weigert @maweigert.bsky.social
* Shalin Mehta @mattersoflight.bsky.social
* Virginie Uhlmann @virginieuhlmann.bsky.social

Meet this year's faculty:

* Alexander Krull
* Anna Kreshuk @ilastik-team.bsky.social
* Constantin Pape @cppape.bsky.social
* Diane Adjavon @adjavon.bsky.social
* Florian Jug @florianjug.bsky.social
...

All you have to bring is a good understanding of python 🐍, enthusiasm to learn with fellow participants, sunscreen 🏖️, and... your own 🔬 data to work on!

👉 Our TAs will help you in the second week of the course to apply what you learnt to your data!

During 14 full days, we will have ample time for lectures, exercises, discussions, and project work.

We will introduce you to deep learning and its applications to image denoising/restoration/translation, semantic and instance segmentation, object detection, tracking, and more!

AI@MBL: Machine Learning for Microscopy Image Analysis | Marine Biological Laboratory The goal of this course is to familiarize researchers in the life sciences with state-of-the-art deep learning techniques for microscopy image analysis and to introduce them to tools and frameworks th...

How can AI help you to analyze your microscopy images?

Find out at the "Machine Learning for Microscopy Image Analysis" course at the @mblscience.bsky.social in Woods Hole from Aug 22-Sep 6!

Applications are due 🚨 April 30 🚨

Read on for more! 👇

www.mbl.edu/education/ad...

‼️🔬 We start!!! 🎉🤖
Super exciting!!! After years of teaching courses for #DeepLearning for Microscopy and Life Science application, we start today our first “advanced course” @embl.org!
#EMBLDeepLearning

How can we use machine learning to find subtle patterns in our data and have them visualized?

Read the thread below to find out how!

Or head to @adjavon.bsky.social's blog post and let Simon the duck walk you through it (like a duck of course): tinyurl.com/yy7csdcd

www.biorxiv.org/content/10.1...

A blue sky

METAR BSKY 181910Z AUTO VRB06KT 10SM CLR 18/03 A2983

(I do like a blue sky ☺️)

Good to see you all again.

🚀 Excited to share our paper has been accepted at #NeurIPS! 🎉 We developed a deep learning framework that infers local learning algorithms in the brain by fitting behavioral or neural activity trajectories during learning. We validate on synthetic data and tested on 🪰 behavioral data (1/5 🧵)