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SciML

@ml_sci

Scientific machine learning group based in @SciComp_STFC - we use ML/AI to push the boundaries of science. Part of UK Research and Innovation https://nitter.cf/t.co/36cvvaZXvk

Joined February 2019
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We have just published the SCD 2021/2022 #AnnualReview!🎉🖥️ Follow the link below to find out what we have been working on recently!👨‍💻🖱️ shorturl.at/pVY34
Image from SciComp_STFC (@SciComp_STFC)
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If you're at #ICNS2022 don't miss the Plenary IV talk today by Toby Perring @isisneutronmuon! Toby and his colleagues have been working with our @ml_sci group to apply machine learning to experiments.
Image from SciComp_STFC (@SciComp_STFC)
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See what's trending in @MLSTjournal right now featuring great work by @VolpeResearch @teodorolaino @reymondgroup @pschwllr @acvaucher @PhilMaffettone @MichaelSFuhrer @JannisBorn @drugilsberg #compchem #machinelearning #datascience #quantum #materials #AI #synchrotron #openscience
Image from Machine Learning: Science and Technology (@MLSTjournal)
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This is sure to be great! Read the fantastic related review by @NArtrith @TobiasMorawietz @GroupKaestner @AlexUrban42 et al in @MLSTjournal at https://nitter.cf/t.co/x3KK9eeggZ #compchem #materials #machinelearning #energy
SciML (@ml_sci) profile pictureSciML@ml_sci24 Nov 2021
This week's SciML @SciComp_STFC seminar (Thurs 13:00 UK) we are excited to welcome @NArtrith talking about Modelling of Complex Energy Materials with Machine Learning - more details on joining: scd.stfc.ac.uk/Pages/SciML-S… - some of Nong's great work here: iopscience.iop.org/article/1…
Image from SciML (@ml_sci)
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9 Distance Measures in data science with algorithms. via: @gp_pulipaka
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And now #OpenAccess in ePubs: purl.org/net/epubs/work/5081… doi.org/10.1063/5.0065694
SciML (@ml_sci) profile pictureSciML@ml_sci10 Nov 2021
Out now in J Chem Phys our work on using graph neural nets with Gaussian processes for active learning of materials properties aip.scitation.org/doi/10.106…
Entropy-based active learning of graph neural network surrogate models for materials properties

Entropy-based active learning of graph neural network surrogate models for materials properties

Graph neural networks trained on experimental or calculated data are becoming an increasingly important tool in computational materials science. Networks once t

pubs.aip.org
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DiRAC Users! Apply now for DiRAC's ML training course which will teach you Python techniques for Scientific Computing. Provided in collaboration with @STFC's @ml_sci. #python #MachineLearning #training #computing #ml #ComputationalScience dirac.ac.uk/machine-learning…
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Visit our virtual exhibition for this year's @Supercomputing conference!🌐 👉stfcvirtual.org/computing/ Find out what #computing can achieve and how @STFC_Matters supports researchers in various fields. There's lots to see👀, including videos, displays and scientific posters #SC21
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Don’t forget to submit your #MachineLearning and #MedicalImaging research in PMB and @MLSTjournal focus issue: ow.ly/NGuC50Grg0K We are specifically looking for high-quality research and advances on ML models in medical imaging
Image from IOPPBio (@IOPPBio)
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There are exciting PhD positions open in my group at @EPFL_en/@EPFL_CHEM_Tweet! Topic: ML for Sustainable Synthesis When: Early 2022 (from February 2022 on) Info: epfl.ch/schools/sb/research/… Apply now and join us right from the start. Retweets appreciated. #ChemTwitter #CompChem
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Great new work by @jlischner597 Gábor Cśanyi, Andrew Horsfield et al @Cambridge_Eng @ImpMaterials @ImperialPhysics @ImperialSci - 'Predicting polarizabilities of #silicon clusters using local chemical environments' https://nitter.cf/t.co/Flxui4gekx #compchem #materials #machinelearning
Image from Machine Learning: Science and Technology (@MLSTjournal)
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I am really excited to share with you our latest work on #diffraction #tomography of a commercially-available cylindrical NMC #liion #battery just published at Small Methods: lnkd.in/du96Tr3p #XRDCT @mat_dorota @FindenLtd @desynews @UCLChemistry @ml_sci @DECTRIS_News
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Register for our 3rd #AI3SDAutumn Seminar Series on Data Science 4 Chemistry! Speakers: @anatmilo of @bengurionu & @SuperScienceGrl of @Syngenta! #DataScience #Data #DataAnalytics #Chemistry #Science @profechem @SamiKanza
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Are you enthusiastic to develop scientific software for neutron applications? A number of open ended positions are now available at @isisneutronmuon . Further information and how to apply will be found here: careersportal.co.uk/UKRI-car… Deadline is 31st October 2021.
Image from UK Neutron Scattering Group (@UkNeutron)
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Free 10 hour machine learning course: https://nitter.cf/t.co/LvzSK8tF4a
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We've openings for a postdoc (Jan 2022 or later) and PhD students (Fall 2022). If you're excited about using computations and data-driven approaches to discover & design new materials, please check out: prashungorai.org/join-the-la… RTs appreciated! #compchem #chempostdoc #postdoc
Image from Prashun Gorai (@prashungorai)
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'Deploying the #BigData Science Center at the Shanghai #Synchrotron #Radiation Facility......#China' by Chunpeng Wang, Alessandro Sepe et al at CAS @STFC_Matters @SciComp_STFC now hits 1500 downloads! https://nitter.cf/t.co/vGpmgAfhOh #datascience #HPC #machinelearning #XFEL #neutrons #AI
Image from Machine Learning: Science and Technology (@MLSTjournal)
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Happy #NationalCodingWeek!🥳 #DYK that members of @ml_sci and @isisneutronmuon used #coding to change the way we interpret data in #materialscience? They programmed computers using #Python to understand materials faster. What took years to classify now takes just weeks!📅
Target Station 2 in ISIS Neutron and Muon Source.

ALT Target Station 2 in ISIS Neutron and Muon Source.

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📢@Bruneluni has #PhD studentship for “Fitting GPU Optimization for materials data” for @isisneutronmuon @RutherfordApLab starting 1st October 2021. Deadline is noon on Friday 4 June 2021 #phdopportunity #PhDposition #Software #GPU #research #materials 👉brunel.ac.uk/research/Resear…
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RTs appreciated: Postdoc positions available in our group! If you have interests in #catalysis, #CO2utilization, #operando spectroscopies, #compchem, #machinelearning, please send your application to [email protected]
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