Stefan P. Schmid

PhD position in machine learning for photocatalysis

We are recruiting a PhD student in machine learning for photocatalysis! In this project, we will collaborate with the group of Frank Glorius @gloriusgroup.bsky.social to develop predictive tools for energy-transfer-catalyzed photocycloadditions.

Reposts appreciated!
jobs.ethz.ch/job/view/JOP...

Hahah nice; but shouldn‘t it be „in silica“ (SiO2)? This would avoid the confusion ;-)

Oxidative amination by nitrogen atom insertion into carbon-carbon double bonds The synthesis of nitrogen-containing molecules through carbon–nitrogen (C–N) bond formation is critical for the discovery and preparation of medicines, agrochemicals, and materials. Here, we report th...

Many Congrats to @ybraegger.bsky.social,
Ann-Sophie Paschke, Nima Nasiri, Bence Botlik
and Francesco Felician for this masterpiece! Oxidative amination by nitrogen atom insertion into carbon-carbon double bonds in Science, @ethzurich.bsky.social.
www.science.org/doi/10.1126/...

🤝 Lastly, huge thanks to the entire team: Ella Rajaonson, @chertianser.bsky.social, Mohammad Haddadnia, @shixuanleong.bsky.social, @aspuru.bsky.social, @agustinus.kristia.de, @valencekjell.com, @felix-s-k.bsky.social

💻 the Code is available openly at github.com/felix-s-k/cu...

Give it a try and let us know what you think!

🔎Lastly, we benchmark different Bayesian Optimization strategies and investigate how they can accelerate the identification of general reaction conditions. As an example, we find that the most efficient CurryBO strategy increases the identified generality 1.5x across a limited number of experiments.

🔎 Once formalized, we show that considering more substrates does indeed give more general reaction conditions that also work better for new substrates. While we augment common HTE datasets with more negative examples to be more realistic, this holds true for almost all datasets.

🔎 We tackle this challenge by formalizing the problem as an optimization problem over a curried function space — a concept from programming that reduces the number of input arguments of a function.

🔎 General reaction conditions are conditions that ‚work well‘ for multiple substrates; useful if you want to synthesize a library of compounds or need a substrate scope. While there is definitely a need for such conditions, noone systematically investigated how to obtain them in a data-driven way

One Set to Rule Them All: How to Obtain General Chemical Conditions via Bayesian Optimization over Curried Functions General parameters are highly desirable in the natural sciences - e.g., chemical reaction conditions that enable high yields across a range of related transformations. This has a significant practical...

🚀 Looking for reaction conditions that work well for multiple substrates? CurryBO can help🍛

Now out on arXiv: arxiv.org/abs/2502.18966

A short explanation thread 👇

Inverse Design of Singlet‐Fission Materials with Uncertainty‐Controlled Genetic Optimization We uncover candidates for singlet fission using a machine learning-driven uncertainty-controlled genetic algorithm (ucGA), which is run either in an exploitative or explorative manner. Leveraging a f...

Inverse Design of Singlet-Fission Materials with Uncertainty-Controlled Genetic Optimization doi.org/10.1002/anie... #compchem

BoTier: Multi-Objective Bayesian Optimization with Tiered Composite Objectives Scientific optimization problems are usually concerned with balancing multiple competing objectives, which come as preferences over both the outcomes of an experiment (e.g. maximize the reaction yield...

My first post here on #bsky – what better occasion than our group's first preprint? BoTier (Multiobjective Optimization with Multiple Tiers of Objectives) is now on arXiv. This project was actually born out of necessity – more details in the 🧵 below. Please check it out!

arxiv.org/abs/2501.15554

Homepage - DCL

Digital Chemistry Laboratory is excited to be on BlueSky 👋

We are a research group at ETH Zurich led by @valencekjell.com that develops digital solutions to chemical problems in catalysis and molecular design 🖥️ 🧪

More about us: dcl.ethz.ch

See you here for the news and research updates!

Come and join a growing and exciting effort at the @uoft.bsky.social on #ai for #materialsdiscovery #chemsky as #assistantprofessor Please reshare massively

PhD position in digital ligand engineering for nanocatalysis

Another chance to join our group! We are recruiting a PhD student in digital ligand engineering for nanocatalysis. Reposts and spreading the word to interested people in your network appreciated!
jobs.ethz.ch/job/view/JOP...

neurips.cc/virtual/2024...

I will be at #NeurIPS next week, presenting work on Bayesian Optimization over curried functions at the AI4Mat workshop. We use it to identify general reaction conditions (see below)

If you are around and interested in talking #BayesOpt or #AI4Science, let’s meet

PhD student - Machine learning in bio- and cheminformatics

Here's a first:
I'm hiring a PhD student.
If you have (or know someone who has) a strong background and interest in computational (bio)chemistry or computer science (especially 3D computer vision), let's work together 😊

www.wur.nl/nl/vacature/...

We are hiring (resharing appreciated)!

Given recent successful grant applications (I got my SNSF Starting Grant 🚀), we are extending the LIAC team with multiple openings (PhD/postdoc) for 2025.

Apply now (deadline: December 20th) by filling in this form: forms.fillout.com/t/eq5ADAw3kkus.
#ChemSky

Could you add me as well please? 💻🧪

Come be my colleague and let‘s do cool science together 💻🧪 Also, ping me if you want to know more about life in the Group and Zurich

Could you add me as well please? Doing AI 4 Chemistry 🧪👨‍🔬