Daniel Armstrong

Exciting postdoc opportunity in the @SchwallerGroup at EPFL! We're hiring a postdoc to advance ML-driven synthesis planning after Zlatko Joncev’s successful exit to co-found B-12 (YC '25) 🚀 Work on: - LLMs for strategic synthesis planning - Chemical reasoning at scale - Building the next-gen framework for retrosynthesis Our recent preprint shows that LLMs can guide synthesis planning with natural-language strategies — combining AI reasoning with traditional chemical tools (arxiv.org/abs/2503.08537). Join us at the intersection of chemistry & AI. Up to 2 years. Based in Lausanne 🇨🇭 Apply: forms.fillout.com/t/nnxVE3RcPpus #ChemTwitter #MachineLearning #SynthesisPlanning #PostdocPosition

Out now! @pschwllr, @SchwallerGroup, @loic_roch, @VictorSabanza and colleagues provide guidelines and recommendations for when to use multi-fidelity Bayesian optimization over their single-fidelity counterparts nature.com/articles/s4358… 🔓rdcu.be/exyUh

Happy to present a poster of my work on starting material constrained synthesis planning, Tango*, in the AI4Materials workshop at #ICLR2025 in 🇸🇬 Thanks to collaborators @JeffGuo__ and @ZJoncev and my PI @pschwllr!

AdsMT is finally out in @NatureComms 🥳 It is designed for rapid prediction of global minimum adsorption energy (GMAE) from surface graphs and adsorbate descriptors. Thanks to @XuHuang461675 , @pschwllr and @NCCR_Catalysis! Paper & code: nature.com/articles/s4146… @SchwallerGroup

Thanks to the co-authors and the Swiss National Science Foundation for supporting this work.

Reaction feasibility is a huge issue in retrosynthesis tools; models often propose reactions which are incompatible with different regions in the molecule. Here the LLM correctly tags the highlighted alcohol group as incompatible with the bromide and suggests MOM/TBS protection.

New LIAC ( @SchwallerGroup ) pre-print out! Here we show that language models understand synthetic strategy, reaction mechanism and chemical structure. Many thanks to my co-authors @drecmb, @TheoNeukomm and @ZJoncev along-with our PI @pschwllr. Paper: arxiv.org/abs/2503.08537

5/ Thanks to my PI @pschwllr (@SchwallerGroup), my collaborators @JeffGuo__ and @ZJoncev, and the Swiss National Science Foundation (@snsf_ch) for funding this work.

4/ We thank developed this work using code and models provided by the Coley Group (@cwcoley) in their recent work, DESP. Code : github.com/coleygroup/desp Paper : arxiv.org/abs/2407.06334

1/ Starting material constrained synthesis planning is now possible using a general retrosynthesis algorithm *without* training a dedicated value network! Check-out our new paper, TangoStar. Preprint : arxiv.org/abs/2412.03424

Another great #Ellis workshop on ML for Molecular Discovery. Thanks to @gklambauer, @fra_grisoni, and the whole organizing team! Proud of our team's contributions - 3 posters (@d_armstr, @kelmannson, @ZJoncev) and an excellent talk by @SarinaKopf! Very well done! #compchem

ChemCrow is finally our in @NatMachIntell! 🥳🔥 nature.com/articles/s4225… It took us more than a year since the preprint, but we made it With @SamCox822 @andrewwhite01 @CarloBalda97 @OSchilter @CarloBalda97 @andrewwhite01 @pschwllr. @EPFL_en @NCCR_Catalysis @FutureHouseSF