Jakob Macke

🚨 We're hiring: Research Coordinator for CRC Robust Vision
@unituebingen.bsky.social

Take a leading role in our DFG funded consortium in neuroscience, ML & CV

MSc/PhD + science mgmt. Apply by Mar 15 👇 join our team w/ @jakhmack.bsky.social @bethgelab.bsky.social

uni-tuebingen.de/en/universit...

Hiring now!
📢 The CRC 1233 Robust Vision consortium at @unituebingen.bsky.social is looking for a Research Coordinator to lead science management, support project execution, and help steer our interdisciplinary research in neuroscience, machine learning and computer vision.

The Brain Prize Course - Computational and Theoretical Neuroscience - CAJAL […]

A special year for the Cajal Course in Computational Neuroscience: the BRAIN Prize winners Haim Sompolinsky and Larry Abbott will join us as keynote speakers. And we will bring you the same great roster of instructors as every year. Applications are now open! cajal-training.org/on-site/comp...

SBI Hackathon Grenoble is a wrap! 🎉

35 researchers and a great hybrid format of 1.5 days of tutorials + 1.5 days of applied hackathon. Many went from “having heard of sbi” to applying full SBI workflows to their own research projects.

🧵👇

Happy 2026 everyone! Two freshly minted PhDs 🧑‍🎓emerged from our lab at the end of last year.
We congratulate Dr Julius Vetter (@vetterj.bsky.social) and Dr Guy Moss (@gmoss13.bsky.social)! Here seen celebrating with the lab 🎳. 1/3

Tübingen AI Research Building, where the Cluster of Excellence "Machine Learning" is based.

📢We’re hiring: W3-Professorship in Machine Learning in Physics @unituebingen.bsky.social! What we’re looking for: Established research profile in a core area of #physics (condensedmatter, quantum or theoretical particle physics), strong track record in research questions related to #ML and/or #AI.

Oops, meant this link: erc.europa.eu/system/files...

Congrats to all the ERC COG recipients, of course especially to the 5 from @unituebingen.bsky.social, and even more so to the @ml4science.bsky.social members @tobiasuhauser.bsky.social and @andreasgeiger.bsky.social (AI assistants!)!!!

erc.europa.eu/system/files...

Come work with us!!!

Finally got the job ad—looking for 2 PhD students to start spring next year:

www.gao-unit.com/join-us/

If comp neuro, ML, and AI4Neuro is your thing, or you just nerd out over brain recordings, apply!

I'm at neurips. DM me here / on the conference app or email if you want to meet 🏖️🌮

English translation (by AI...):
Question:
How can generative AI contribute to supporting education and science? (Multiple answers possible)
Answer:
It can help in science by automatically generating new and innovative research approaches.

We were asked to do an online training on 'AI awareness' by admin. I almost failed the test, as I was not aware of some of the fundamental limitations of #AI4Science.

Not going to NeurIPS Nor Eurips, but the lab is showing cool new work on SBI and differentiable biophysics, do check it out and talk to them (we also have open positions …)!

* spatial models-- which come up in geosciences and many other applications, given, well, the geometry of the world we live in.

@gmoss13.bsky.social et al sending SBI to space 🚀*!!!

We are having a lot of fun and excitement both with fancy new AI methods and shiny fly connectomes … and those ERC euros make that possible!

lthough technically „has grown“ is not quite correct — we graduated, or will graduate soon, equally many brilliant PhDs ;-)

AI tool for brain simulations links cellular detail to cognitive functions — MACHINE LEARNING for science For decades, brain simulations have either been largely simplified, or they could not perform cognitive tasks. A new AI tool opens possibilities to build brain simulations that can achieve both.

On our blog: For decades, brain simulations have either been largely simplified, or they could not perform cognitive tasks. #JAXLEY, a new AI tool, opens possibilities to build brain simulations that overcome both limitations: www.machinelearningforscience.de/en/jaxley-ai... #AIforScience

Possibly the best part of the job: The amazing students and scientists we get to work with!

Simulation-based inference has really become a commonly used tool for parameter inference across many fields and applications. We (finally...) got together to write a tutorial introduction and guide to (hopefully) help users get started and navigate the different methods and diagnostics!

Jaxley: differentiable simulation enables large-scale training of detailed biophysical models of neural dynamics - Nature Methods Jaxley is a versatile platform for biophysical modeling in neuroscience. It allows efficiently simulating large-scale biophysical models on CPUs, GPUs and TPUs. Model parameters can be optimized with ...

I am super happy to share that our project on training biophysical models with Jaxley is now published in Nature Methods: www.nature.com/articles/s41...

Great new work from the labs of @jakhmack.bsky.social and @philipp.hertie.ai! The software Jaxley enables brain simulations which both imitate the processes in the brain in detail and can solve challenging cognitive tasks. Press release of @unituebingen.bsky.social: uni-tuebingen.de/en/universit...

Congrats to @deismic.bsky.social and everyone for getting this out!

An ion channel omnimodel for standardized biophysical neuron modelling Biophysical neuron modeling is an indispensable tool in neuroscience research, with the combination of diverse ion channel kinetics and morphologies being used to explain various single-neuron propert...

“Mapping ion channel function” doi.org/10.7554/eLif... isn’t exactly a citation slayer, but it’s still one of my favourites (& my first independent project). Today we push pt 2, where we trace code origin & unite almost all channel models in a common expression. Boom! www.biorxiv.org/content/10.1...

🎉 sbi participated in GSoC 2025 through @numfocus.bsky.social and it was a great success: our two students contributed major new features and substantial internal improvements: 🧵 👇

Hello Frankfurt 🇩🇪 - We are excited to share the latest result from our group and collaborators at
@bernsteinneuro.bsky.social 🚀🧠 #BernsteinConference

Thanks to @brainloops.bsky.social, @ekfstiftung.bsky.social and @cherish-msca.bsky.social for supporting these projects and our scholars.

The Macke lab is well-represented at the @bernsteinneuro.bsky.social conference in Frankfurt this year! We have lots of exciting new work to present with 7 posters (details👇) 1/9

From hackathon to release: sbi v0.25 is here! 🎉

What happens when dozens of SBI researchers and practitioners collaborate for a week? New inference methods, new documentation, lots of new embedding networks, a bridge to pyro and a bridge between flow matching and score-based methods 🤯

1/7 🧵

Sharing this here a bit late, but @vstaros.bsky.social and I wrote a little something about our experience contributing to the @sbi-devs.bsky.social (simulation-based inference) hackathon. @mlcolab.org @mackelab.bsky.social

We were obviously very hungry while writing.

My first paper on simulation-based inference (SBI) as part of @mackelab.bsky.social!

Exciting work on adapting state-of-the-art foundation models for posterior estimation. Almost plug-and-play, and surprisingly effective.

Paper/code in thread below 🧵