🚨 Want to join us?
- We offer 5 postdoc positions in European projects in València
- ML/DL, #Earth science, #hybrid modelling, #climate model #parametrization, #UQ, #diffusion & #foundation models
- Apply by Aug 1st 2024: https://t.co/hnAtT8q4L7
Happy summer! 🌊🌞🥘⚽️
🚨New preprint🎉
"Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales"
https://t.co/FbfxNyeDvA
An absolute pleasure working on this during my internship @nvidia with @NoahBrenowitz @SciPritchard@JaideepPathak@tropmetpie and others 🧵
📢Excited to share I've successfully defended my thesis at @oxcsml and will be joining @eapsMIT this summer as a postdoctoral associate🌍
Many thanks to my examiners @nicholls_geoff and Tom Beucler, to my supervisor @sejDino, and to @DWatsonParris for making this possible!
🌟 It’s a great honour that our work has been selected as a spotlight paper for #ICML2024 ! This work offers a new perspective on Domain Generalisation so check it out!
Many thanks to collaborators @_anurags14@shbouabid@krikamol!
I want to thank my wonderful co-authors @DWatsonParris @sejDino@iMIRACLI_ITN, but also @maybritt_sch and three anonymous reviewers for their great quality feedback on this work!
📢🥳FaIRGP is out!
It's a mathematically tractable and easy-to-use probabilistic ML emulator of surface temperatures that uses FaIR as its backbone. This hybrid model improves over purely physics or data-driven emulators with uncertainty quantification!
https://t.co/Go7nb99FYa
📢Happy to share our latest work with @sejDino @DWatsonParris : FaIRGP, an emulator that combines the robustness of simple climate models and the flexibility and uncertainty quantification of GPs.
📰Preprint: https://t.co/yeR39yUQNs
💻Code: https://t.co/MXKypss7hX
⏬More below
🚨 Our #ICML2024 paper contends that domain generalisation encompasses both statistical learning and decision-making. Learners are thus compelled to make normative judgments, leading to misalignment amidst institutional separation from model operators.
@icmlconf
⚠️New paper out⚠️
Excited to share the publication of our latest work on the response of clouds to shipping emissions🚢
Satellite retrievals + modelled shipping pollution = insights into aerosol-cloud-climate change interactions.
On the academic job market this year? @CISPA offers an exciting opportunity to conduct world-class research with generous research support.
🚨 Tenure-Track Faculty in Artificial Intelligence and Machine Learning (f/m/d)
RT Please 🙏
https://t.co/DIkoBtQXFf
Its hard to overstate just how exceptionally high global temperatures are at the moment. They have blown past anything we've previously experienced by a huge margin.
Over at The Climate Brink, we try and visualize this summer of extremes in seven charts. https://t.co/yApwMbyxgG
Il y a 48h, une étude scientifique publiée annonçait que la 6ème limite planétaire sur 9 était désormais officiellement dépassée... et ce fut un vrai raz de marée médiatique !
Non bien sûr, comme d'habitude, tout le monde s'en fout.
📢Post-doc opening in Adelaide with Prof. Dino Sejdinovic @sejDino 📢
I highly recommend working with Dino, who was one of my supervisors during my PhD in Oxford :)
Consider applying if you want to do a great post-doc in sunny Australia !
https://t.co/oV6M0DzcP4
By gaining trust in such a data-driven yet physically grounded model, we hope the climate science community can benefit more widely from their potential.
📢Happy to share our latest work with @sejDino @DWatsonParris : FaIRGP, an emulator that combines the robustness of simple climate models and the flexibility and uncertainty quantification of GPs.
📰Preprint: https://t.co/yeR39yUQNs
💻Code: https://t.co/MXKypss7hX
⏬More below
Finally, FaIRGP is easy-to-use (analytical expressions throughout), can naturally account for climate internal variability and provides principled uncertainty quantification through its Bayesian treatment.