Joshua W. Sin

PhD student @Roche @SchwallerGroup | Previously @duarte_group @OxfordChemistry

[Siu Lun Chau @Chau9991]

🚨 PhD opportunity!

I’m recruiting a PhD student with a strong background in math/stats/CS to join my group at NTU Singapore 🇸🇬
Start: Jan or Aug 2026
Topic: Foundations of Epistemic Uncertainty in ML 🧠🔍
📌 Details: https://t.co/k0lCzXNfAt

RT appreciated!

[Rebecca Neeser @RebeccaNeeser]

Hello from Singapore 🇸🇬! Thrilled to be at #ICLR2025 presenting our work on fragment-based drug discovery 🧩. We go beyond virtual screening with a generative, structure-aware approach.
📃 https://t.co/rH6SkSCPIY
🔗 https://t.co/H8BTPGLZp8
A thread 🧵👇

[BOjana Ranković @6ojaHa]

🚨New preprint!
✨My precious✨ GOLLuM: GP-Optimized LLMs for Bayesian Optimization — the first of its kind!
LLMs as deep kernels in GPs jointly optimized via marginal likelihood → implicit metric learning, calibrated uncertainty & superior sampling 🚀
📄 https://t.co/hqJuUzT88Q

[Daniel Armstrong @d_armstr]

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 : https://t.co/hVG1r3f6fa

[Philippe Schwaller (he/him) @pschwllr]

We are hiring (resharing appreciated)!

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

Are you interested in #AI4Science and machine learning with real-world applications in chemistry?

Apply now (deadline: December 20th) by filling in the following form: https://t.co/iTDjnMNIWX. Interviews with selected candidates will take place in January/February.

We offer a highly dynamic and collaborative environment with competitive salaries (https://t.co/OQtVfGxjfk) and benefits (https://t.co/pSFV8N3Fff).

We strongly encourage candidates of all different backgrounds and identities to apply. Each new hire is an opportunity for us to bring in a different perspective, and we are always eager to further diversify our team.

Check out https://t.co/0Rk0KOMLN9.

[Rebecca Neeser @RebeccaNeeser]

FSscore has now been published in Chemistry-Methods (@ChemEurope)! 🚀
Check out the updated paper on personalized synthesizability scoring here:
https://t.co/4H2JeeZjtF

[Jeff Guo @JeffGuo__]

General-purpose (without any constraints) molecular generative models can *directly* optimize for *constrained* synthesizability using retrosynthesis models!

Find out why it *takes two to tango*:

Pre-print: https://t.co/0jOoPWvTwu
Code: https://t.co/5DkPdPZZpE

(1/2)

[Víctor Sabanza Gil @VictorSabanza]

1/ 🧪💡 Curious about faster material & molecular discoveries? Multi-fidelity Bayesian Optimization (MFBO) is your friend! In this paper, we investigate when MFBO is truly effective compared to standard BO methods, helping to balance cost & accuracy in optimization campaigns.

[Joshua W. Sin @jwpsin]

By integrating machine intelligence with HTE robots, we aim to accelerate reaction optimisation in both academia and the pharmaceutical industry.

(3/3)

[Joshua W. Sin @jwpsin]

Excited to share our preprint on a scalable ML optimisation framework applied to automated HTE reaction optimisation in highly parallel batches!

preprint: https://t.co/bdRdnIZyzQ

Thanks to my PI @pschwllr (@SchwallerGroup) and @Roche for this exciting collaboration!

(1/3)

[Joshua W. Sin @jwpsin]

We applied this machine learning workflow experimentally to a 96-well HTE optimisation of a nickel-catalysed Suzuki reaction, showcasing advantages over traditional, purely experimentalist-driven HTE plate design in navigating complex reaction landscapes.

(2/3)