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  1. Beginner Learn to Ride Class

    The Environmental Sustainability and Energy Team at LJMU have received funding from Cycling UK to carry out a number of events for the Big Bike Revival.

  2. Beginner Learn to Ride Class

    The Environmental Sustainability and Energy Team at LJMU have received funding from Cycling UK to carry out a number of events for the Big Bike Revival.

  3. Beginner Learn to Ride Class

    The Environmental Sustainability and Energy Team at LJMU have received funding from Cycling UK to carry out a number of events for the Big Bike Revival.

  4. Beginner Learn to Ride Class

    The Environmental Sustainability and Energy Team at LJMU have received funding from Cycling UK to carry out a number of events for the Big Bike Revival.

  5. Dr Bike Clinic

    The Environmental Sustainability and Energy Team at LJMU have received funding from Cycling UK to carry out a number of events for the Big Bike Revival.

  6. Get into Teaching Online Open Day

    Attend our Get into Teaching Online Open Day to ask questions to our academics and admissions teams to learn more about how you can begin your teacher training journey.

  7. ARI Seminar: Nikhil Sarin (Stockholm University)

    A neutron star binary merges somewhere in the Universe approximately every 10 to 1000 seconds, creating violent explosions potentially observable in gravitational waves and across the electromagnetic spectrum. The transformative coincident gravitational wave and electromagnetic observations of the binary neutron star merger GW170817 gave invaluable insights into these cataclysmic collisions and fundamental astrophysics. However, despite our high expectations, we have failed to see any other event like it. In this talk, I will highlight what we can learn from other observations of mergers seen directly in gravitational waves or indirectly as a gamma-ray burst and/or kilonova. I will also discuss the diversity in electromagnetic and gravitational-wave emission we can expect for future mergers and showcase tools to help maximally extract physics from existing and future observations.