One open role I'm especially excited for is an expert physicist/material scientist to help us bring quantum effects to the real world.
Help us develop first-principles quantum simulations that will be physically tested in our autonomous lab.
Our team at DeepMind is growing (again). 🚀
We're tackling grand challenges in semiconductors, magnets, energy materials, superconductors, and beyond.
Join us! Two positions below.
Our team at DeepMind is growing.
We've assembled a world class physics+material science team and are building an experimental lab.
If you want to solve real problems at the intersection of AI + material science to unlock a technological revolution - this is the place. Apply 👇
The entire NSF research budget is ~$9B/year. This is literally funding every awarded PI at every field and every institution.
But we've decided that all of basic science is a rounding error in comparison to venture bets.
Please consider funding basic science more.
Delighted to welcome Prof. Umesh V. Waghmare, Professor & Dean, Faculty Affairs, JNCASR, as the new President of JNCASR. He assumed office on 11 June 2025. Prof. G.U. Kulkarni handed over charge to Prof. Waghmare at a ceremony at the President’s Office today.
@waghmare16
Our team at GDM is hiring a software engineer to help us build the future of AI-driven scientific discovery. 🚀
If you want to work with us on scaling scientific simulations, AI agents, and our latest training runs, come join us!
At @GoogleDeepMind, our world-class team of quantum materials experts, engineers, and AI researchers is using massive-scale compute and AI to revolutionize materials discovery.
We're expanding! We are looking for truly exceptional computational materials scientists. 👇
I am excited to announce what @LiamFedus and I have been working on: @periodiclabs, a world class team of experimentalists, theorists, and LLM experts.
Scientific discovery is inherently an out-of-domain task. Experimental iteration is required for significant advances, regardless of the form of intelligence that is modeling the world. We are building experimental labs that will unlock the next frontier for LLM reasoning.
Deeply grateful to our advisory board, Prof. Carolyn Bertozzi, Prof. Mercouri Kanatzidis, Prof. Steven Kivelson, Prof. Zhi-Xun Shen, and Prof. Chris Wolverton, for their guidance and support.
Sharing this very unique materials science role with @GoogleDeepMind. They are looking specifically for someone to build a materials lab with them from the ground up. Time is short, deadline to apply in Jul 22!
"We are seeking an exceptional and highly motivated expert in solid-state synthesis and characterization to lead the design, outfitting, and management of this new laboratory. This is a founding role with a unique blend of scientific leadership, hands-on experimental work, and strategic input. You will be instrumental in building our experimental capabilities from the ground up and refining the critical in-silico to experiment feedback loop that is at the heart of our mission."
🧪🔬 Synthesis experts!
Our team at Google DeepMind is hiring a scientist to establish and lead an AI-driven laboratory for materials discovery.
The team is working to combine our AI capabilities with automated experimentation to discover novel functional materials. 1/
🧠 Interested in pushing the scientific frontier with LLM post-training and RL? Our team is hiring a Research Engineer at Google DeepMind to accelerate materials science! 💡 Join us: https://t.co/4BvUkvUbvd
🚨 Our team at GDM is hiring a research engineer to work on topics around RL, post-training + materials science! Role is based in Mountain View. DMs open if you have questions.
Happy to introduce AlphaGenome, @GoogleDeepMind's new AI model for genomics.
AlphaGenome offers a comprehensive view of the human non-coding genome by predicting the impact of DNA variations. It will deepen our understanding of disease biology and open new avenues of research.
@Robert_Palgrave Sorry, this is very funny to me, because people who are actually domain experts here are jumping in to criticize them in exactly the way you jumped in to criticize things in your own domain. I think you might have Gell-Mann Amnesia here.
A very nice perpective on our recent approach to predicting crystal structures from amorphous precursors using deep learning potentials, by Prof. Schön.