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Linda Ulmer

@lulmer.bsky.social
101 followers 158 following 1 posts

PhD student @mackelab.bsky.social - machine learning and computational neuroscience

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Reposted by Linda Ulmer
Machine Learning in Science @mackelab.bsky.social · 28/09/2026
The Macke lab is back at @bernsteinneuro.bsky.social in Frankfurt! 🧠🪰 This year with 2 satellite workshop talks + 5 posters on mechanistic, connectome-constrained models of the fruit fly. All posters are joint work with @srinituraga.bsky.social. Come and say hi! 👋 Details 👇 (1/8)
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Sven Dorkenwald @sdorkenw.bsky.social · 17/09/2026
Applications are now open for the San Juan Winter School 2027 on Connectomics and Brain Simulation! Join us to learn how to analyze and simulate connectomes. sjcabs.com
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John Tuthill @tuthill.bsky.social · 24/03/2026
🧵 New preprint led by @bingbrunton.bsky.social, @elliottabe.bsky.social, @lawrencehu.bsky.social We gave a worm brain control of a fly body and it walked What did we learn? Nothing, other than deep reinforcement learning is effective We call it the digital sphinx www.biorxiv.org/content/10.6...
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Linda Ulmer @lulmer.bsky.social · 11/03/2026
Looking forward to presenting our work on connectome-constrained modeling at #cosyne2026
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Richard Gao @rdgao.bsky.social · 03/12/2025
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 🏖️🌮
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Reposted by Linda Ulmer
Machine Learning in Science @mackelab.bsky.social · 28/11/2025
We are looking for a Research Engineer (E13 TV-L) to work at the intersection of #ML and #compneuro! 🤖🧠 Help us build large-scale bio-inspired neural networks, write high-quality research code, and contribute to open-source tools like jaxley, sbi, and flyvis 🪰. More info: www.mackelab.org/jobs/
mackelab.org
Jobs - mackelab
The MackeLab is a research group at the Excellence Cluster Machine Learning at Tübingen University!
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Reposted by Linda Ulmer
Machine Learning in Science @mackelab.bsky.social · 13/11/2025
Our work on training biophysical models with Jaxley is now out in @natmethods.nature.com. Led by @deismic.bsky.social, with @philipp.hertie.ai, @ppjgoncalves.bsky.social & @jakhmack.bsky.social et al. Paper: www.nature.com/articles/s41...
nature.com
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 ...
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Reposted by Linda Ulmer
Machine Learning in Science @mackelab.bsky.social · 30/09/2025
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
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Richard Gao @rdgao.bsky.social · 23/09/2025
I've been waiting some years to make this joke and now it’s real: I conned somebody into giving me a faculty job! I’m starting as a W1 Tenure-Track Professor at Goethe University Frankfurt in a week (lol), in the Faculty of CS and Math and I'm recruiting PhD students 🤗
media.tenor.com
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ALT: a man wearing a white shirt and tie smiles in front of a window
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sbi - Simulation-based inference @sbi-devs.bsky.social · 09/09/2025
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 🧵
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sbi - Simulation-based inference @sbi-devs.bsky.social · 12/05/2025
Great news! Our March SBI hackathon in Tübingen was a huge success, with 40+ participants (30 onsite!). Expect significant updates soon: awesome new features & a revamped documentation you'll love! Huge thanks to our amazing SBI community! Release details coming soon. 🥁 🎉
A wide shot of approximately 30 individuals standing in a line, posing for a group photograph outdoors. The background shows a clear blue sky, trees, and a distant cityscape or hills.
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Machine Learning in Science @mackelab.bsky.social · 30/04/2025
🎓Hiring now! 🧠 Join us at the exciting intersection of ML and Neuroscience! #AI4science We’re looking for PhDs, Postdocs and Scientific Programmers that want to use deep learning to build, optimize and study mechanistic models of neural computations. Full details: www.mackelab.org/jobs/ 1/5
mackelab.org
Jobs - mackelab
The MackeLab is a research group at the Excellence Cluster Machine Learning at Tübingen University!
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Reposted by Linda Ulmer
Auguste Schulz @auschulz.bsky.social · 03/02/2025
1) Some exciting science in turbulent times: How do mice distinguish self-generated vs. object-generated looming stimuli? Our new study combines VR and neural recordings from superior colliculus (SC) 🧠🐭 to explore this question. Check out our preprint doi.org/10.1101/2024... 🧵
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Janne Lappalainen @lappalainenjk.bsky.social · 30/12/2024
Ever wanted to do deep learning with a neural net that is one-to-one mapped to 65.05% of the fruit fly brain? 😄 Before this year ends, I will quickly advertise our code release of `flyvis.` Docs: t.ly/YqWzR Repo: t.ly/pMWpp Work with @jakhmack.bsky.social, @srinituraga.bsky.social and colleagues
Screenshot of the docs at turagalab.github.io/flyvis
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Reposted by Linda Ulmer
ML for Science @ml4science.bsky.social · 20/12/2024
Can we build neural networks whose structure and computational abilities match a real brain? We are not quite there yet, but recent work by @lappalainenjk.bsky.social et al. shows a strategy for getting closer to this goal. Read more on our blog: www.machinelearningforscience.de/en/improving...
machinelearningforscience.de
How a tiny animal helps us improve brain simulations with AI
Can we build neural networks whose structure and computational abilities match a real brain? We are not quite there yet, but our new paper shows a strategy for getting closer to this goal.
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Reposted by Linda Ulmer
sbi - Simulation-based inference @sbi-devs.bsky.social · 27/11/2024
The sbi package is growing into a community project 🌍 To reflect this and the many algorithms, neural nets, and diagnostics that have been added since its initial release, we have written a new software paper 📝 Check it out, and reach out if you want to get involved: arxiv.org/abs/2411.17337
arxiv.org
sbi reloaded: a toolkit for simulation-based inference workflows
Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a significant challeng...
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