Come work with me on generative models for materials at CuspAI! We have: - a fantastic team lead by @wellingmax.bsky.social and @aronwalsh.github.io - important problems and fun methods - offices in beautiful Amsterdam, Cambridge, London, Berlin jobs.ashbyhq.com/cuspai/b8108...

Applied ML Researcher (Generative Models)

Due to growth, we are seeking an experienced Applied ML Researcher (Generative Models)* to join our growing team and build SOTA generative models to design new materials at CuspAI.

jobs.ashbyhq.com

Scaling Laws in Particle Physics Data! This is a result I've been itching to share and it's finally out. One of the big open questions is how much better AI-based methods at particle colliders can still become. 1/4

Happy New Year! Do your plans for 2026 include... - working with a great team lead by @wellingmax.bsky.social and @aronwalsh.github.io? - living in Amsterdam, Berlin, London, or Cambridge? - using fun tools from ML and material science? - solving important problems? Then join us at CuspAI! 1/2

Come work with us at @cuspai.bsky.social in the generative model team! Excited about flow / diffusion models and chemistry? Looking for impact? jobs.ashbyhq.com/cuspai/b8108... Join a great team lead by @wellingmax.bsky.social and Aron Walsh, work in Amsterdam / Cambridge / London / Berlin. 1/2

Applied ML Researcher (Generative Models)

Due to growth, we are seeking an experienced Applied ML Researcher (Generative Models)* to join our growing team and build SOTA generative models to design new materials at CuspAI.

jobs.ashbyhq.com

Today at NeurIPS (SD), come meet the @cuspai.bsky.social team and learn about our work! Find us at 5:30pm at booth 1343 (Renaissance Philanthropy / UK government)

As we go into the Thanksgiving holiday, I wanted to express my thanks to my collaborators @johannbrehmer.bsky.social @glouppe.bsky.social, Juan Pavez, @smsharma.bsky.social. Recently, I was awarded the Pritzker Prize for AI in Science for work on SBI. That wouldn't have never happened without them.

I'll be at NeurIPS next week – together with my @cuspai.bsky.social colleagues @jonkhler.argmin.xyz, @hannahopenshaw.bsky.social, Friso de Kruiff, and @wellingmax.bsky.social. If you'd like to chat about ML for material discovery, generative models, or start-ups made in Europe, ping me!

It was great to work on the ODAC25 paper with the Meta FAIR Chemistry and Georgia Tech. A leap forwards in modelling direct air carbon capture with metal organic frameworks, with much better data and larger models. Paper: arxiv.org/abs/2508.03162 Data and models: huggingface.co/facebook/ODA...

The Open DAC 2025 Dataset for Sorbent Discovery in Direct Air Capture

Identifying useful sorbent materials for direct air capture (DAC) from humid air remains a challenge. We present the Open DAC 2025 (ODAC25) dataset, a significant expansion and improvement upon ODAC23...

arxiv.org

Are you tired of context-switching between coding models in @pytorch.org and paper writing on @overleaf.com? Well, I’ve got the fix for you, Neuralatex! An ML library written in pure Latex! neuralatex.com To appear in Sigbovik (subject to rigorous review process)

An unexpected surprise. The 2025 Breakthrough Prize in Fundamental Physics honors over 13,000 researchers whose labors have led to the precise description the Higgs mechanism, … breakthroughprize.org/News/91 @CERN

On March 7th, we’re Standing Up for Science— and against political censorship, autocracy, and fascism. Science stands at a crossroads. This is a wider fight for truth, for democracy, and for the future. We hope you join us. www.standupforscience2025.org

STAND UP FOR SCIENCE

March 7, 2025. Washington DC and nationwide. Because science is for everyone.

standupforscience2025.org

📣 Hiring! I am looking for PhD/postdoc candidates to work on foundation models for science at @ULiege, with a special focus on weather and climate systems. 🌏 Three positions are open around deep learning, physics-informed FMs and inverse problems with FMs.

Excellent talk by @johannbrehmer.bsky.social On “Does equivariance matter at scale?” At NeurReps workshop arxiv.org/abs/2410.23179 www.neurreps.org

Just arrived in Vancouver for #NeurIPS. I'm looking forward to meeting old and new friends, learning a thing or two, and presenting some recent work: 1/6

A common question nowadays: Which is better, diffusion or flow matching? 🤔 Our answer: They’re two sides of the same coin. We wrote a blog post to show how diffusion models and Gaussian flow matching are equivalent. That’s great: It means you can use them interchangeably.

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

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...

arxiv.org

Thrilled to announce that L-GATr is going to NeurIPS 2024! Plus, there is a new preprint with extended experiments and a more detailed explanation. Code: github.com/heidelberg-h... Physics paper: arxiv.org/abs/2411.00446 CS paper: arxiv.org/abs/2405.14806 1/7

GitHub - heidelberg-hepml/lorentz-gatr: Repository for <Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics> (J. Spinner et al 2024)

Repository for <Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics> (J. Spinner et al 2024) - heidelberg-hepml/lorentz-gatr

github.com

Milestone: our review paper “The Frontier of Simulation-Based Inference” coauthored with @glouppe.bsky.social & @johannbrehmer.bsky.social hit 1000 citations. I’m very excited about the potential for these methods to transform science! www.pnas.org/doi/10.1073/... simulation-based-inference.org

The snow is gently falling outside the window, the models are training, what could be better? Two articles cool to read: Does Equivariance matter at scale? (@johannbrehmer.bsky.social et al.) arxiv.org/abs/2410.23179 Denoising Diffusion Bridge Models (Linqi Zhou et al.) arxiv.org/pdf/2309.16948

Looking for an internship? Interested in geometric or causal priors for robotics, inductive biases at scale, or one of many other ML topics? Come work with us in Amsterdam! careers.qualcomm.com/careers?pid=...