We aim to set the global standard for a truly interdisciplinary approach to contemporary data-driven research challenges. Established in 2015, the Data Science Institute (DSI) has over 300 members and has raised over £37 million in research grants.
Research ThemesThis workshop aims to bring together researchers interested in environmental and ecological statistical modelling to discuss advances in, 和未来的, the two disciplines and to investigate potential synergies
We hope to provide a platform for discussion and collaboration between applied and methodological statisticians, data scientists, scientists and policy makers, across all career stages and regardless of affiliation.
If you analyse or develop statistical models for environmental and ecological data then this workshop is for you. Specific statistical methods include, but are not limited to, spatio-temporal modelling, downscaling, time-series analysis, hierarchical modelling
There is no charge to attend, however we ask that anyone who plans on attending the should register for the workshop. We have capacity for up to 50 people, so if you need to pull out after registering, please let us know so that we can re-open your space.
If you cannot make the full workshop but would like to attend parts, please register and use the free text `Any other information’ box to say which days you can attend.
In addition to invited talks and discussion sessions, we would like to receive contributed presentations from those in the earlier stages of their careers. We are loosely defining this to be PhD students and anyone who is 5-years or less post-PhD. If you are unsure whether you fit into this category, please get in touch.
The workshop will take place in the Postgraduate Statistics Centre at Lancaster University.
The organisers are Emma Eastoe and Alex Bush
The aim of the workshop is to review recent progress in discerning cyclic processes in noisy backgrounds, focusing especially on the widespread case of oscillations with time-varying frequencies. Pedagogical lectures will be combined with hands-on practical sessions and possibilities to discuss problems and new directions with a range of invited experts.
Topics
Submission To propose a poster please submit an abstract (maximum 1 page) to tsand@step1method.com. Details are given on the conference website.
Important Dates Expression of interest: 1st of August Registration: 15th of August Abstract submission: 8th of September
Registration See details on the conference website: http://wp.lancs.ac.uk/tsand/
Within the Data Science Institute, our aim is to improve the reproducibility and replicability of research by improving the reusability, sustainability and quality of research software developed across the University. We are currently funded by the N8CIR, and work closely with our partner institutions across N8 Research.
Research Software Engineering
Data Science at Lancaster was founded in 2015 on Lancaster’s historic research strengths in Computer Science, Statistics and Operational Research. The environment is further enriched by a broad community of data-driven researchers in a variety of other disciplines including the environmental sciences, health and medicine, sociology and the creative arts.
Foundations research sits at the interface of methods and application: with an aim to develop novel methodology inspired by the real-world challenge. These could be studies about the transportation of people, goods & services, energy consumption and the impact of changes to global weather patterns.
The Health theme has a wide scope. Current areas of strength include spatial and spatiotemporal methods in global public health, design and analysis of clinical trials, epidemic forecasting and demographic modelling, health informatics and genetics.
Data Science has brought new approaches to understanding long-standing social problems concerning energy use, climate change, crime, migration, the knowledge economy, ecologies of media, design and communication in everyday life, or the distribution of wealth in financialised economies.
The focus of the environment theme has been to seek methodological innovations that can transform our understanding and management of the natural environment. Data Science will help us understand how the environment has evolved to its current state and how it might change in the future.
Professor Christina Pagel gave a talk to DSI on 'What Independent SAGE has taught me about the current biggest issues in light of COVID-19 and where data science can help'. Listen here to her insights and observations about the ongoing pandemic.
A recording is now available of the launch of the book by Amy Clair and our very own Jasmine Fledderjohann and Bran Knowles entitled, "A Watershed Moment for Social Policy and Human Rights?: Where Next for the UK Post-Covid". The event included an overview of the key concepts and themes in the book; invited talks from Aaron Reeves (University of Oxford), Kayleigh Garthwaite (University of Birmingham), and Daniel Greene (University of Maryland).
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