On "science that is greater than the sum of its parts", the post hits on key ingredients:
+ understanding of problems from multiple perspectives and across multiple dimensions;
+ pragmatic engineering for high-quality execution;
+ touching the real world, doing it at scale;
+ demonstration and iteration, always;
that can together enable "execution-driven science." In practice, much of that R&D progress is posted at https://pasteur4d.ai/research and other offshoots of https://arxiv.org/pdf/2112.03235
At Pasteur Labs, we develop computing technologies that enable scientific and industrial challenges to be approached in new ways: that is, a first of its kind AI-native, developer-first platform for modeling & simulation (M&S). Our product aim is to enable in-silico playgrounds for human-machine teams experimenting and building in industrial R&D, energy security, & advanced manufacturing arenas. As a public-benefit for-profit startup, our mission is Nobel-Turing [1] technologies to advance science and society for all humankind. With venture funding and Fortune500 customers (+dozens more on the waitlist), we’re looking for ambitious, intellectually curious software engineers that can consistently contribute in non-trivial, impressive ways as we ship and scale our flagship product platform — some call it “live intelligent digital twins” and others say “cyberphysical testbeds for AGI”, while most view Pasteur Labs product catalogue as “Databricks for industrial R&D”.
--> https://pasteurlabs.ai/careers/ <-- While we don’t list requirements for degrees or years-experience, everyone needs to demonstrate high-caliber engineering and problem-solving; we’re dedicated to scientific rigor and robust engineering for complex and dynamic environments, so prove to us that you not only fit in but that you can make us better. In particular, we are seeking experienced DevOps / MLOps teammates that can build from day 1 with Go, Python, containerization, and our multiple cloud setups (Azure, Google (GCP), Oracle Cloud (OCI)), and on-prem infrastructure for mixed GPU & CPU workloads — if you've done this before with CAE simulation systems and scientific datasets, reach out and say so!
Our team is largely made of industry-hardened research-software engineering experts [2], whom thrive in interdisciplinary and fast-paced teams—from NASA to Nvidia, Deepmind to Oracle, CERN to Cerebras, SpaceX to Autodesk, the Navy, Air Force, and on. With HQ in Brooklyn NY [3], and satellite offices opening in Copenhagen + London + Vancouver in 2025, we are an internationally distributed team running remote full-time — from San Francisco to Sao Paulo to Stockholm and everywhere in-between. The full team gathers multiple times per year for 1-week Pasteur Labs “onsites”—recently in Miami, Amsterdam, Cambridge, and more.
If what we’re doing speaks to you, please get in touch! Send your CV/resume and other supporting info/demos/etc to us at careers@simulation.science
[1] https://arxiv.org/pdf/2112.03235.pdf
[2] https://us-rse.org/about/what-is-an-rse/
[3] http://newlab.com