groznyj

also, append `?tune` for fun times!

Atomscale | Software Engineer, Full Stack | Boston, MA (Hybrid Onsite) | https://atomscale.ai

Atomscale is building AI to improve atomic-scale materials manufacturing. Our goal is to help translate new materials into new technologies and products by making sure they can be created at scale instead of stalling at R&D.

This is a hard (but exciting!) challenge that involves high-throughput data ingestion and processing pipelines, complex data visualization, and hardware integrations for direct control. The payoff is unlocking new technologies that address today's most pressing challenges.

⎯

We're looking for a Product-oriented Software Engineer that will:

- Build ergonomic interfaces for data visualization, workflow automation, and AI-copilot assistance.

- Develop backend systems with flexible, expressive data models and performant APIs.

- Create desktop apps for on-premises low-latency data streaming and hardware integrations.

(You don't need background in materials science!)

⎯

More details: https://www.atomscale.ai/careers/software-engineer-full-stac...

To apply: email jobs@atomscale.ai with the job title + HN

Atomscale | Software Engineer, Full Stack | Boston, MA (Hybrid Onsite) | https://atomscale.ai

Atomscale is building AI to improve atomic-scale materials manufacturing. Our goal is to help translate new materials into new technologies and products by making sure they can be created at scale instead of stalling at R&D.

This is a hard (but exciting!) challenge that involves high-throughput data ingestion and processing pipelines, complex materials science data visualization, and hardware integrations for direct synthesis control. The payoff is unlocking new technologies that address today's most pressing challenges.

⎯

We're looking for a Product-oriented Software Engineer that will:

- Build ergonomic interfaces for data visualization, workflow automation, and AI-copilot assistance.

- Develop backend systems with flexible, expressive data models and performant APIs.

- Create desktop apps for on-premises low-latency data streaming and hardware integrations.

(You don't need background in materials science)

⎯

More details: https://www.atomscale.ai/careers/software-engineer-full-stac...

To apply: email jobs@atomscale.ai with the job title + HN

Atomscale | Applied AI/ML Engineer | Boston, MA (Hybrid Onsite) | https://atomscale.ai

Atomscale is building AI to improve atomic-scale materials manufacturing. Our goal is to translate new materials into new technologies and products by ensuring they can actually be created at scale faster and cheaper.

This is a hard (but exciting!) challenge that involves hardware integrations, AI that understands materials data, and real-time dynamic intervention during processing.

⎯

We're looking for an Applied AI/ML Engineer that will help:

- Develop new models to analyze materials processing data

- Improve systems for model infra & deployment

- Build data engineering pipelines to handle large amounts of multimodal data

(You don't need background in materials science)

⎯

More details: https://www.atomscale.ai/careers/applied-ai-ml-engineer

To apply: email jobs@atomscale.ai with the job title + HN

Hey HN, reframing things in terms of experiments has been super motivating for me and wanted to share my thoughts on it.

I think this approach could be described as "experimentation over self-belief".

One reason it's powerful is that it solves the self-belief bootstrapping problem: when you don't have self-belief, how can you take actions which require it, in order to develop it?

You can always do an experiment.

Happy user [0] of Bear Blog [1], would recommend.

I would also recommend spending less than 30 minutes setting up a blog if you have less than 4 posts written. [2]

[0] https://thrice.me/

[1] https://bearblog.dev/

[2] https://www.benkuhn.net/writing/#set-up-your-blog

Hi HN,

A few months ago I was training for a marathon and learned some exercise physiology to try and improve how I train.

I wrote an article to synthesize that learning and "relaunched" it on a Bear blog today. Wanted to share it here to get some feedback and hopefully spread some knowledge. Let me know what you think!