Proud to present Denoising Diffusion Models, where we connect the learned score of a diffusion model with force fields to do sampling and simulations🎉 Work done during a wonderful collaborative internship @MSFTResearch@JCIM_JCTC https://t.co/B28kqTFvd2, https://t.co/KsVJgYjm7Z
After 3.5 years of ups and downs, I successfully defended my PhD thesis about generative models for proteins, and got this awesome hat created by the lovely @KU_BioML group 🤠 I feel grateful and inspired to keep working in this exctiting field! Thesis: https://t.co/3btutHpKZV
Check out this new paper on representation learning on protein sequences by Nicki Skafte Detlefsen, Søren Hauberg & @WouterBoomsmaDK! 👇
A great collaboration through the #MLLS center (https://t.co/QPO1sp9Eak).
I'm very happy to share our work on representation learning of protein sequences, just out in @NatureComms.
This was a joint project with Nicki Skafte Detlefsen and Søren Hauberg through the #MLLS center (https://t.co/FD2x6tolYt). 1/5
https://t.co/3ttompvPlU
Open PhD position on machine learning for protein engineering. Collaboration between @pengfei10, @deboramarks and myself - hosted @Novozymes. Great opportunity to work on non-trivial problems with non-trivial methods.
Interested in fundamental research in machine learning - motivated by problems in biology? Our newly established MLLS center in Copenhagen has 6 open PhD positions. Deadline Feb 25. https://t.co/C3mUQYQtFi. Please RT.
Hi everyone! We are the BioML group (https://t.co/yq41WlEJfp), led by @WouterBoomsmaDK and located at @DIKU_Institut@uni_copenhagen. We apply #ML techniques to biological problems and are particularly interested in the link between protein sequence, structure and function.