Jordan Dorrell

Postdoctoral Research Associate in AI/Ml-Driven Chemical Discovery - Grade 7 at University of Liverpool Apply now for the Postdoctoral Research Associate in AI/Ml-Driven Chemical Discovery - Grade 7 role on jobs.ac.uk - the leading job board for higher education jobs. View details.

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Join us as a Postdoctoral Research Associate in AI/ML-Driven Chemical Discovery
Work at the intersection of AI, machine learning & chemistry on cutting-edge research.
📍 Liverpool | ⏰ Apply by 20 Feb 2026
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Please repost if you’re in the area of #AI or #chemistry. Funded by EPSRC. #chemsky

"a "Hive Mind" method that connects autonomous laboratory robots with human scientists and AI agents".

Sounds exciting! Will you have multiple people per hive mind or just one human with a flock (what's the collective noun?) of robots/AIs?

I have a three-year PDRA position to work on the development of adaptive embedding methods. Please share this with anyone who may be interested. #CompChem www.ucl.ac.uk/work-at-ucl/...

Hierarchical Crystal Structure Prediction of Zeolitic Imidazolate Frameworks Using DFT and Machine-Learned Interatomic Potentials Crystal structure prediction (CSP) is emerging as a powerful method for the computational design of metal-organic frameworks (MOFs). In this article we demonstrate the high-throughput exploration of t...

During my PhD I had the pleasure of collaborating with the Arhangelskis group to do CSP on MOFs. Most of the work here was done by Yizhi (Catherine) Xu who generated and optimised MOFs with up to 16 formula units!
The preprint is online now!
arxiv.org/abs/2601.05097

#compchem #csp

If we switch to GUIs, the experimentalists might realise how easy we have it!

Super excited to get this preprint online with @graemeday.bsky.social !

With SAUCE, we significantly improve on the efficiency of random structure searching for crystals containing multiple symmetry-independent molecules!

chemrxiv.org/engage/chemr...
#compchem #csp

If I've misunderstood anything, I do apologize. Please correct me in the thread. Overall I think the paper's going to do very well and I look forward to reading the final print! 12/12

reduce the number of force evaluations required per optimisation, then their method is likely to be overall cheaper than contemporary CSP methods and I would expect to see the model as a strong contender in the next CSP blind test. 11/12

There is one final point in which I think that they're probably *under*selling their work. The accuracy of their generated structures is likely to improve if optimised with DFT. If their model can reduce the number of structures that need to be optimised, and 10/12

I'd really like to see how the model compares to the blind test participants using the 7th blind test's criteria for a match. I would also be really interested to see how Sol_c changes with the number of crystals generated and also the number of symmetry-independent molecules. 9/12

They do summarise the performance of each group for every target in their SI but they haven't reported the performance of OXtal on each target so we can't compare. 8/12

If they're averaging over each group's performance, that's flawed in the other way because the best performing groups/methods are impeded my the lower performing groups/methods. 7/12

If they're counting a successful prediction by any group as a success for "DFT-based submissions" then they're probably being overly generous to DFT because they're sampling across an ensemble of different DFT approaches. 6/12

They compare their model initially to other generative models on CSD structures but later compare their performance against a "aggregate of reported expensive DFT-based submissions" for previous CSP blind tests. I'm not entirely sure how they're aggregated though. 5/12

In the preprint, the criteria for "approximately solved" (Sol_c) was an RMSD of less than 2 Å for a cluster of 15 molecules (a significantly looser tolerance). They're not using the word "match" here, but it really feels implied that that's what they have. 4/12

The authors use the @ccdc.cam.ac.uk's COMPACK metric to overlay crystals and minimise the RMSD between clusters of N molecules. COMPACK is also used in the CSP blind tests but in the latest blind test, the criteria for a match was an RMSD of less than 1 Å for a cluster of 30 molecules. 3/12

Unfortunately, the data as presented makes me feel that the claims made by the authors are somewhat exaggerated. I'm particularly concerned with the metrics which are described as "standard CSP metrics". 2/12

"OXTAL: AN ALL-ATOM DIFFUSION MODEL FOR
ORGANIC CRYSTAL STRUCTURE PREDICTION" was put into preprint (arXiv:2512.06987) this weekend! We've seen some decent generative models for inorganic CSP but this model marks a big step forward for generative models for organic crystals!
1/12 #compchem

Schematic of an evolutionary algorithm for generating new organic molecules, with crystal structure prediction integrated into the fitness function calculation.

I'm excited to share the latest paper from our team, just published in Nature Communications: rdcu.be/eRTSs

"Exploring organic chemical space for materials discovery using crystal structure prediction-informed evolutionary optimisation"

#compchemsky #chemsky

1/n

New addition for the Day group office?

Choose comp-chem and you won't even have to go into the office!

Just about ready for our first workshop on mol-cspy: our source software for crystal structure prediction
gitlab.com/mol-cspy/mol...
A massive thank you to the research team in getting material together for this.
#compchemsky #chemsky

Farage vows to scrap indefinite leave to remain, placing thousands at risk of deportation Reform UK plans to force non-citizens to apply for visas with high salary thresholds and no access to NHS services

Thousands of Londoners have indefinite leave to remain.

They have legal rights and are our friends, neighbours and colleagues, contributing hugely to our city.

Threatening to deport people living and working here legally is unacceptable.

Strange way to ask what sector of science people work in.

I had a fantastic time at the #MMMHub conference this week. I had some really great conversations!

Thank you to all the attendees who voted me runner up for the best poster prize.

I hope to come back next time to talk about even more innovations in crystal structure prediction!

Debuting my bsky.social account with a photo from the first day of the 2025 Materials and Molecular Modelling (MMM) Hub conference at @keeleuniversity.bsky.social . Thrilled to be the local organiser for this exciting event.

A dreary Tuesday morning in Southampton but excited for the #MMMHub conference this afternoon! If you want to hear what I've been up to with @graemeday.bsky.social , I have a talk today at 15:40 and I'm poster number 7!
#compchem

Image of speaker at conference in front of projected slide showing computer simulation results on molecular crystals.

Thank you to the organisers of the "from molecules to materials" meeting in Bologna for inviting me to give a keynote talk.
Among other things, I spoke about @aichemyhub.bsky.social-funded large-scale crystal structure prediction and transferable ML potentials: doi.org/10.1039/D4FD...
#compchemsky

Article doesn't mention anything about the UK being bad for research. Merck just complains that the UK doesn't pay enough for drugs and that Trump is pressuring them to invest in US facilities instead.