Eli Weinstein

PhD scholarship in Machine Learning for Molecules - DTU Chemistry Advance large scale data generation for chemical and biological AI in a 3 year PhD. Work on the frontier of active learning, and develop novel probabilistic machine learning techniques for experiment ...

I'm looking for my first PhD student! We will push the frontiers of probabilistic machine learning for the molecular sciences, and study how to design new algorithms that exploit the unique properties of molecular systems to learn about the world.

efzu.fa.em2.oraclecloud.com/hcmUI/Candid...

So excited about this - we did iterative generative design at large scale with variational synthesis, and got human scFv candidates against some of the hardest therapeutic targets around.

🔊 The call for the first round of open PhD fellowships from the newly formed Danish Advanced Research Academy (DARA) has just been announced:

daracademy.dk/fellowship/f...

Exceptional candidates with a strong background in theoretical chemistry are more than welcome to reach out to me for support.

We can make population genetics studies more powerful by building priors of variant effect size from features like binding. But we’ve been stuck on linear models! We introduce DeepWAS to learn deep priors on millions of variants! #ICML2025 Andres Potapczynski, @andrewgwils.bsky.social 1/7

If you are interested in working with me as a student or postdoc, or otherwise collaborating, please reach out.

Thrilled to announce that I am joining DTU in Copenhagen in the fall, as an assistant professor of chemistry.

My research group will focus on fundamental methodology in machine learning for molecules.

The BayesComp workshop on 'Bayesian Computation and Inference with Misspecified Models' will take place in Singapore on the 16-17th June.

We have an open call for posters/contributed calls, with a deadline on the 1st May. More details on the website:
postbayes.github.io/BayesMisspec...

Calendar - Machine Learning - CMU - Carnegie Mellon University Calendar of the Machine Learning Department at Carnegie Mellon University

This Thursday, 1PM, @eweinstein.bsky.social is headed back to CMU, this time to the Machine Learning Department. He'll be sharing his work on hierarchical causal models. If you're on campus, I encourage to you check it out!

www.ml.cmu.edu/calendar/

Tomorrow -- another chance to learn about variational synthesis, probabilistic experimental design methods, & ways to capture scaled functional data for model training: this time with zoom access for those of you remote, 1pm at @cmu.edu Computer Science. Details at:

www.cs.cmu.edu/calendar/181...

Today at UPenn's CIS Seminar: a chance to hear about variational synthesis, probabilistic experimental design methods, and ways to capture modern ML-scale functional data for biology: events.seas.upenn.edu/event/13596/

1/n I'm thrilled to share *Deep generative modelling of the human proteome reveals over a hundred novel genes involved in rare genetic disorders* t.co/DoN4DrSFbS from a wonderful collaboration between the Marks Lab and Dias and Frazer group, with @roseorenbuch as lead! 🧵:

The news came out! Last week we signed a deal with the fantastic team at Replay Bio and their product company Syena to develop a KRAS G12D specific therapeutic TCR therapy. So proud and excited!

www.businesswire.com/news/home/20...