UKRI Centre for Doctoral Training in Biomedical AI
@BioMedAI_CDT
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Training next generation of innovators at the interface of AI, biomedicine and social science @InfAtEd
Edinburgh, Scotland
Joined July 2019
📢🧬Looking for fast and reliable ways to predict binding affinities? Meet BALM!👋 BALM predicts binding affinity from protein sequences and ligand SMILES using pretrained protein and ligand language models. 📄 https://t.co/t79Gdlq9Mx 🔗 https://t.co/hnsfgOvY3j 🧵1/9
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Great opportunity for a Business Development Executive wishing to join @AI4BI_CDT and @EdinInnovations to work on ambitious projects at the interface of AI and biomedicine
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⭐️ Fully-funded PhD studentship in biomedical NLP ⭐️ - open now - https://t.co/O4EYoJcBe8. In this project we will be developing methods to combine the power of LLMs and ontologies to improve harmonisation of data in healthcare in collaboration with Roche.
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As part of our Outreach Programme, Fiona Smith's amazing art installation at ARS Electronica Festival for Art, Technology and Society in Linz was, to quote a visitor, "a beautiful balance between the hard data and the softer human elements.."
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Let me introduce: InstanSeg 🦠🔬💻👩🔬 This *would* have been a short thread about Thibaut Goldsborough’s PhD work… but he solved too many problems. Now it's a long thread about 2 preprints, a whole new approach to cell segmentation & #opensource software to make it easy to use
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Congratulations Ben Philps on winning the MIUA 2024 Best Paper Award! Well done supervisors María del C. Valdés Hernández and Miguel Bernabeu and Antonio Vergari👏
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Currently recruiting for a PhD student in a collaboration with @Roche and Honghan Wu @UofGlasgow - https://t.co/EgwRk9CNLl as part of the @AI4BI_CDT using LLMs in healthcare.
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Fantastic news for first year PhD student Aryo Pradipta Gema!
Fine-tune your LLM unless you have access to GPT-4! In our SemEval 2024 @NLI4CT solution, we evaluated LLMs with ICL, CoT, and a novel PEFT method. And yet, GPT-4 produces surprisingly good results, ranking joint-first in the leaderboard! 👉 https://t.co/XC1iWBwU43 🧵 1/9
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Applications are now open to join our new UKRI AI Centre for Doctoral Training in Biomedical Innovation for September 2024 entry. All the information you need to apply is ➡️ https://t.co/W7g5miBZ0j
@UKRI_News @AI4BI_CDT
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We're very much looking forward to hosting the 2024 Conference in AI for Healthcare (CAI4H) on 20 and 21 May in Edinburgh with partners @AI4HealthCentre, @cdt_ai_health -health, and @LeedsMedAI_CDT
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🗓️#BioEng24 Conference May 6/7 #future #medicine 📪Abstract deadline - March 31st 📨REGISTER yourself by sending YOUR abstract 📪 https://t.co/hLHW4I4rhH -JOIN international speakers in #imaging #organoids #multiomics #stemcells #geneengineering #synthetic #biology #AI and more
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Congratulations Rohan Gorantla on your recent publications. 👏👏👏 https://t.co/YzDJjgmhzQ
pubs.acs.org
Active learning (AL) has become a powerful tool in computational drug discovery, enabling the identification of top binders from vast molecular libraries. To design a robust AL protocol, it is...
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🎉🚀 Excited to share that my internship work, "Benchmarking Active Learning Protocols for Ligand Binding Affinity Prediction," has been published in ACS @JCIM_JCTC! 🔗 https://t.co/QezFgYuQpd Find 🧵 below for a quick overview. @exscientiaAI
pubs.acs.org
Active learning (AL) has become a powerful tool in computational drug discovery, enabling the identification of top binders from vast molecular libraries. To design a robust AL protocol, it is...
📢🚀Thrilled to share preprint of my internship work @exscientiaAI “Benchmarking Active Learning Protocols for Ligand Binding Affinity Prediction” 👉 https://t.co/J9ZmjuBJS7 💻 We study the influence of various AL parameters and dataset features for identifying top binders. 🧵1/9
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Congratulations Rik Sarkar and Rayna Andreeva, whose paper “Machine learning and Topological data analysis identify unique features of human papillae in 3D scans” is being published. See the preprint here: https://t.co/PEReo2OMzV a University of Leeds collaboration.
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🧵1/5🚨Preprint alert🚨We @bryanlimy @DHidalgoMazzei @tetraduzione are happy to share our preprint on self-supervised learning for acute mood episode detection with wearable data: https://t.co/keAwK67yuc
@BioMedAI_CDT @ancAtEd @InfAtEd
arxiv.org
Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a...
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I will be giving a short talk on our spatiotemporal Transformer approach to the #NeurIPS2023 Sensorium challenge this Friday afternoon!
NeurIPS Sensorium Competition workshop is happening on Friday from 1:30–4:30 in room 357. Explore with us the state of the art and future of predictive models of neural responses. Keynotes by @dyamins, Colin Conwell and @s_y_chung
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We have an open faculty position in Machine Learning at the University of Edinburgh for next year. If you are at #NeurIPS2023, reach out to Antonio @tetraduzione to learn more. Closing date: 15th Jan 2024 Apply here: https://t.co/TyiaprSsIA
elxw.fa.em3.oraclecloud.com
Applications are invited for an academic position in machine learning in the School of Informatics at the University of Edinburgh, one of the largest centres in Machine Learning and Artificial...
Calling all Machine Learning researchers on the academic job market for 2024. 📢📢📢 Applications are invited for a full time academic position in Machine Learning in the School of Informatics at the University of Edinburgh.
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