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DTSTART;TZID=UTC:20260914T000000
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SUMMARY:Data Intensive Science School
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE14 – 16 SEPTEMBER 26 ACADEMIC PARTICIPANTS£75 INDUSTRY PARTICIPANTS£150 \n\n\n\nApplications closed\n\n\n\n View agenda \n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nUniversity of Liverpool CampusRendall Building\, Liverpool\, L69 7WW \n\n\n\n\n\n\n\n\n\n\n\n\nJoin AIchemy Hub and LIV.INNO for an intensive hands-on Data Science School designed to equip researchers\, students\, and innovators with practical skills at the intersection of AI\, scientific computing\, and open-source research.This interdisciplinary programme brings together experts from academia and industry to deliver workshops and talks covering modern data science workflows\, scalable computing\, machine learning\, agentic AI systems\, scientific software development\, and research reproducibility.Participants will gain practical experience using cutting-edge tools and frameworks while exploring how AI and data-driven approaches are transforming scientific discovery.The school combines hands-on workshops\, interactive tutorials\, and expert-led talks focused on real-world scientific and data-intensive applications. \n\n\n\n\n\nWho should apply\n\n\n\nThis school is designed for: \n\n\n\n\nPhD students and Early Career Researchers\n\n\n\nData scientists and computational researchers\n\n\n\nScientists interested in AI and machine learning\n\n\n\nResearchers working with large or complex datasets\n\n\n\nAnyone interested in modern open-source scientific computing\n\n\n\n\nWhat you’ll gain\n\n\n\nParticipants will: \n\n\n\n\nGain practical experience with modern data science tools \n\n\n\nLearn directly from experts in AI and computational science \n\n\n\nBuild skills in scalable computing and scientific software development \n\n\n\nExplore emerging trends in agentic AI and open-source science \n\n\n\nNetwork with researchers across disciplines\n\n\n\n\n\n\nProvisional Programme \n\n\n\n\nApache Spark Workshop (4 hours) – Learn scalable data processing and distributed computing techniques for handling large scientific datasets.\n\n\n\nMachine Learning: Data Collection & Preparatio (4 hours) – Explore the foundations of building robust ML pipelines\, from data acquisition to preprocessing and feature engineering.\n\n\n\nAgentic AI for Data Analysis (1 hour talk) Discover how autonomous AI agents are reshaping data analysis\, scientific workflows\, and research productivity.\n\n\n\nGit Workshop (2 hours) Develop essential version control skills for collaborative coding\, reproducible research\, and software development.\n\n\n\nOpen Source Science (1 hour talk) Examine the growing importance of open-source ecosystems in accelerating scientific innovation and collaboration.\n\n\n\nPyAutoFit Workshop (2 hours) Introduction to probabilistic modelling and automated model fitting using PyAutoFit for scientific applications.\n\n\n\nPublishing Code (2 hours) Learn best practices for sharing\, documenting\, packaging\, and publishing scientific software and research code.\n\n\n\nReal World Challenges Session (2 hours) – Apply your skills to practical scientific and data-driven problems inspired by current research challenges.\n\n\n\nHow Not to Make NumPy Slow (2 hours) Improve performance and efficiency in scientific Python workflows through optimisation strategies and vectorised computation.\n\n\n\n\n\n\nSpeakers & Trainers \n\n\n\n\n\nDr Edward BennettSwansea University\n\n\n\n\n\nDr Prakriti KayasthaUCL\n\n\n\n\n\nDr Bradley MartinUCL\n\n\n\n\n\nDr James NightingaleNewcastle University\n\n\n\n\n\n\n\nDr Louise ButcherSTFC/Hartree\n\n\n\n\n\nDr Abdoulatif CisseUniversity of Liverpool\n\n\n\n\n\nDr Alex HillUniversity of Liverpool\n\n\n\n\n\nProfessor Reecha SofatUniversity of Liverpool\n\n\n\n\n\n\n\n\n\n\n\nAccommodation and Travel\n\n\n\nPlease note that the registration fee does not include accommodation\, travel or subsistence. Participants are responsible for arranging their own accommodation and transport during the Data Science School. \n\n\n\nWe are happy to recommend the Novotel Liverpool Paddington Village\, a modern hotel conveniently located within walking distance of the University of Liverpool campus. This hotel offers comfortable rooms\, breakfast options and easy access to local amenities. \n\n\n\nA social networking event will be hosted on one evening during the school and is included in the registration. \n\n\n\nFor those seeking alternative options\, Liverpool offers a wide range of hotels\, serviced apartments\, and budget accommodations within easy reach of the University. \n\n\n\nLiverpool is well-connected by rail\, with Liverpool Lime Street Station approximately a 10-minute walk from the University campus. For those travelling by car\, parking is available at the Paddington Village Car Park\, located close to the University and the recommended hotel. \n\n\n\nAirports:\n\n\n\n\nLiverpool John Lennon Airport (LPL) – Around 30 minutes from the University by taxi or public transport. The airport offers flights to many UK and European destinations.\n\n\n\nManchester Airport (MAN) – Around 1 hour by train or car\, with direct rail connections to Liverpool Lime Street. This airport provides a wide range of international flight options.\n\n\n\n\n\n\n\n\nHow to Apply:\n\n\n\nPlaces are limited and to ensure a balanced mix of expertise and perspectives we are asking applicants to apply. As demand is expected to be high\, we ask all interested participants to complete the application form by 10th July 2026 and decisions will be given to applicants by 17th July 2026. \n\n\n\nPlease note: all bookings are non-refundable. \n\n\n\n\n\n\n\nContact details:\n\n\n\nFor questions related to this event please contact the AIchemy project management team at info@aichemy.ac.uk. \n\n\n\n\n\n\n\n\nThe Organising Committee:\n\n\n\nAlchemy HubLIV.INNODr. Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool)Dr. Alex HillNaomi Smith
URL:https://aichemy.ac.uk/event/data-intensive-science-school/
CATEGORIES:Training School
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