Linda Ulmer
@lulmer.bsky.social
📤 89
📥 148
📝 1
PhD student
@mackelab.bsky.social
- machine learning and computational neuroscience
Looking forward to presenting our work on connectome-constrained modeling at
#cosyne2026
add a skeleton here at some point
9 days ago
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reposted by
Linda Ulmer
Richard Gao
4 months ago
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
4 months ago
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/
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Jobs - mackelab
The MackeLab is a research group at the Excellence Cluster Machine Learning at Tübingen University!
https://www.mackelab.org/jobs/
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reposted by
Linda Ulmer
Machine Learning in Science
4 months ago
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...
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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 ...
https://www.nature.com/articles/s41592-025-02895-w
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reposted by
Linda Ulmer
Machine Learning in Science
6 months ago
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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reposted by
Linda Ulmer
Richard Gao
6 months ago
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 🤗
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reposted by
Linda Ulmer
sbi - Simulation-based inference
6 months ago
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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reposted by
Linda Ulmer
sbi - Simulation-based inference
10 months ago
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. 🥁 🎉
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reposted by
Linda Ulmer
Machine Learning in Science
11 months ago
🎓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
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Jobs - mackelab
The MackeLab is a research group at the Excellence Cluster Machine Learning at Tübingen University!
https://www.mackelab.org/jobs/
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reposted by
Linda Ulmer
Auguste Schulz
about 1 year ago
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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reposted by
Linda Ulmer
Janne Lappalainen
about 1 year ago
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
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reposted by
Linda Ulmer
ML for Science
about 1 year ago
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...
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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.
https://www.machinelearningforscience.de/en/improving-brain-simulations-with-ai/
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reposted by
Linda Ulmer
sbi - Simulation-based inference
over 1 year ago
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
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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...
http://arxiv.org/abs/2411.17337
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