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Heidi Theimann

The Open University

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Variable Stars in the SuperWASP all Star Survey

My PhD is focused on finding and characterising unusual stars, in high volume astronomical data sets. From a catalogue of 1.6 million light curves of variable stars from the SuperWASP all sky survey, I have identified unique eclipsing binary stars using a combination of data science techniques, citizen science, and observational astronomy.

Industry Placement

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As a DISCnet student, I’ve had many opportunities to develop data science skills, especially related to statistics and machine learning to big data. I am hoping to apply these skills to my third year DISCnet placement in the aerospace and defence sector. It has been incredibly valuable to be part of a network of data scientists and researchers, sharing experience and learning from one another.

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DISCnet has not only given me the tools for research, but also the tools to apply data science to real-world applications. This year, I have co-founded a new think-tank, the Space Skills Alliance, which will tackle the lack of good data on the state of UK space industry skills shortage, which will support evidence based policy making in the sector.

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© 2024 by DISCnet 

DISCnet is the Data Intensive Science Centre in SEPnet, and an STFC Centre for Doctoral Training;  

a collaboration between the University of Sussex, Queen Mary University of London, and The Open University

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