Join 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.
Who should apply
This school is designed for:
- PhD students and Early Career Researchers
- Data scientists and computational researchers
- Scientists interested in AI and machine learning
- Researchers working with large or complex datasets
- Anyone interested in modern open-source scientific computing
What you’ll gain
Participants will:
- Gain practical experience with modern data science tools
- Learn directly from experts in AI and computational science
- Build skills in scalable computing and scientific software development
- Explore emerging trends in agentic AI and open-source science
- Network with researchers across disciplines
Provisional Programme
- Apache Spark Workshop (4 hours) – Learn scalable data processing and distributed computing techniques for handling large scientific datasets.
- Machine Learning: Data Collection & Preparation (4 hours) – Explore the foundations of building robust ML pipelines, from data acquisition to preprocessing and feature engineering.
- Agentic AI for Data Analysis (1 hour talk) Discover how autonomous AI agents are reshaping data analysis, scientific workflows, and research productivity.
- Git Workshop (2 hours) Develop essential version control skills for collaborative coding, reproducible research, and software development.
- Open Source Science (1 hour talk) Examine the growing importance of open-source ecosystems in accelerating scientific innovation and collaboration.
- PyAutoFit Workshop (2 hours) Introduction to probabilistic modelling and automated model fitting using PyAutoFit for scientific applications.
- Publishing Code (2 hours) Learn best practices for sharing, documenting, packaging, and publishing scientific software and research code.
- Real World Challenges Session (2 hours) – Apply your skills to practical scientific and data-driven problems inspired by current research challenges.
- How Not to Make NumPy Slow (2 hours) Improve performance and efficiency in scientific Python workflows through optimisation strategies and vectorised computation.
Speakers & Trainers – To be announced
Accommodation and Travel
Please 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.
We 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.
A social networking event will be hosted on one evening during the school and is included in the registration.
For those seeking alternative options, Liverpool offers a wide range of hotels, serviced apartments, and budget accommodations within easy reach of the University.
Liverpool 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.
Airports:
- Liverpool 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.
- Manchester 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.
How to Apply:
Places 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 24th August 2026 and decisions will be given to applicants by 31st October 2026.
Please note: all bookings are non-refundable.
Contact details:
For questions related to this event please contact the AIchemy project management team at info@aichemy.ac.uk.
The Organising Committee:
| Alchemy Hub | LIV.INNO |
| Dr. Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool) | Dr. Alex Hill Naomi Smith |
