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#MachineLearning #ClimateScience #AIResearch #WeatherAI #DataScience #GenerativeAI #ResearchJobs

-Track record of applying ML to weather and climate science
-Drive to push the boundaries of environmental AI applications
Bonus expertise:
-Experience with multi-modal weather datasets
-Hands-on work with generative AI and transformer architectures

If interested in reading about it in detail, please have a look at our arxiv article here:
arxiv.org/abs/2408.10958

Haha this is surely fun! 😂

Yes it is indeed a large array with quite a good number of channels and thus we went with zarr. I think zarr is of course more optimized for large tensors but the benefit also shows up in smaller tensors as they are easily scalable data format, similar to HDF.

We have been experimenting with NVIDIA DALI for deep learning training and inference work with Pytorch and zarr-enabled data loaders. It really has optimized our training and inference pipeline.

github.com/NVIDIA/DALI

Would be happy to be a part of it! 🙂

I wish to specially thank @mikepritchard.bsky.social for giving me the opportunity to work with and learn from his team at NVIDIA. I surely have learnt so much during one year of my postdoc tenure here at NVIDIA. 🙏🏽

Will be happy to be on the list! 🙂

There definitely are a bunch of ML based air quality models out there right now. I believe Microsoft’s Aurora also has that capability if you want to give it a try! 🙂

Thank you Katharine! That sounds wonderful! 🙏🏽

Hey Nathanael! I guess it was about time 😂