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Paul Higgins
Postdoctoral Researcher

Contact
Web: http://pohuigin.wordpress.com/
Email: pohuigin@gmail.com
Skype: mysiriusface

Bio
Through the amazing programs at both Contra Costa College and UC Berkeley in California, I recieved a solid foundation in physics and astrophysics. Berkeley also allowed me the opportunity to explore science public outreach through UniverseAdventure.org working with Prof. George Smoot and Dr. Michael Barnett, and the physics of the Aurora working with Dr. George Parks. Since then, I moved on to Trinity College Dublin in Ireland, where I recently completed my PhD within the Astrophysics Research Group (as of early 2013) under the supervision of Prof. Peter Gallagher. I have worked on SolarMonitor.org, designed data analysis software for the Hinode and Proba2 missions, and currently serve as a Max Millennium Chief Observer. I have also continued by public outreach work, as I am currently leading the development of a Zooniverse citizen science project on sunspots. Now, I am funded under the IRCSET Enterprise Partnership Scheme through 2014. Within the scheme, Trinity has partnered with the Lockheed Martin Solar and Astrophysics Laboratory (LMSAL) in Palo Alto, California and I will spend the majority of my time there, working with other world leading researchers on solar activity.

Research
My main research interests concern the evolution of magnetic fields rooted beneath the surface of the Sun, over the time-scales of minutes (eruptive flares) to days (emerging and evolving sunspot groups) to years (the 11-year sunspot cycle). My thesis is an investigation of solar magnetic fields on these three scales. As a research fellow, I am improving our current flare forecasting capabilities by investigating how sunspot groups 'talk' to each other through their magnetic field connections in the solar atmosphere, and how this chatter leads to increased flare activity. Also, I am involved in an international collaboration to compare current sunspot group characterisation techniques, using state of the art image processing techniques, to improve our flare prediction accuracy.