▲ 0 r/quantum+1 crossposts

Where is my place? Quantum theory postdoc wants to ride on AI wave

hey folks, I am a quantum theorist currently doing a postdoc.

TLDR: I'm currently automating a big part of my research workflow, so I’m wondering how someone with domain science like me could be useful in AI-driven research.

The thing is this, I'm not really looking for generic advice in "academia vs industry". More like: I want to continue what I do know, but at larger scale, how does someone with my profile actually get into big tech or AI labs, and where would I even start?

Broadly speaking I'm working on quantum materials, many-body physics, quantum optics, that kind of stuff. I am interested in novel quantum materials and physical systems that could matter for quantum sensing, semiconductors, energy, information storage, etc. and in my group we are also collaborating heavily with experimental groups. I also took a couple of lectures on deep learning, so I am not totally clueless there, but my main thing is still quantum theory. The reason I am asking is that more and more of my daily work I can automate by agents, and honestly I love it; I used to spend lots of time carefully writing cluster jobs, setting up saving, caching, array jobs, parameter scans, all the annoying details you need so the whole thing does not break after running for 3 days. I used to code quite a lot in C and C++, plus some Python for plotting. Now I can do a lot of this with AI and it is often better, faster, and less error prone than what I wrote myself. Of course, you need to configure your harness and put lots of saveguards, tests, physical consistency checks etc, but it works. Not perfectly, obviously, but the direction is pretty clear. So while the progress has been rather slow the last decades in my field (my impression), I think this could explode now, and the route from basic research to applications could accelerate to a great extend.

So I am wondering if there is a real niche here? Something like an AI babysitter for scientific research, but not "train another model" (I know I have 0 chance to enter this job market and I have 0 ambition). More like someone who knows the quantum theory, knows what equations are actually realistic to do, knows how to formulate the models and sanity check the outputs, and then uses agent systems to scale the boring parts. Literature, numerics, parameter scans, code, simulations, maybe even parts of theory exploration. Do big tech companies or AI labs or companies that I don't know about actually hire people for this kind of thing? Domain scientists who are not pure ML engineers, but can move AI driven scientific research in physics, materials, quantum, scientific computing, etc?

Honestly I always thought I would stay on the standard academic path with some Postdoc positions, papers, then PI position, group, grants, the whole thing. And I do love academia. But in fact I also do not want to miss out on the moment where the actually impactful parts of scientific research moves somewhere else, because they have the compute and the ressources.

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u/vsilv — 5 days ago

Codex complete garbage now - using Deepseek flash to clean up behind mess created by codex

hey folks,

I'm wondering if you have the same issues. I have an openai-pro subscription, which worked extremely well in opencode until this week, when it started to turn my code into complete garbage. It stopped working very often in the middle of coding, and I think during these incidents it just forgot what it was doing and left a mess behind. Maybe they run out of money and quantized their models into int4? No idea.

Anyhow, surprisingly, I have extremely positive experience with deepseek flash (free) from opencode zen. As it turns out, it manages to find many bugs that codex seems to have produced during my last sessions. I always try to keep the "vibe" part of my codebasis limited to some degree, but it's really surprising what kind of havock codex created in a short amount of time. Deepseek flash is not very efficient, so it needs a lot of trivial "thinking" to come up with solutions and to find the problems, but in the end, it's quite effective; and I also checked each file individually to see what was happening and how it dealt with the problems. You have to check it and make sure the plans are fine, but in the end it works out surprisingly well.

What are your experiences; similar? Or did I somehow configure something stupidly?

best,

v.

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u/vsilv — 2 months ago