Dark Energy
In 1998, two experiments discovered that the universe's rate of expansion is accelerating. Since then, physicists have come up with a multitude of different ways that this could be happening. All of these mecahnisms essentially give rise to the same accelerating universe on large scales, but will have slightly different properties on smaller scales. The first project in this field was aimed at trying to write down a general theory to encompass as many other theories as we could, in the form of an effective field theory. We found that such a theory could be described using nine functions.

A Class of Effective Field Theory Models of Cosmic Acceleration
Jolyon Bloomfield and Éanna É. Flanagan
Journal of Cosmology and Astroparticle Physics 10 (2012), 039
arXiv:1112.0303 (2011)
It turns out that there is a much more powerful method to investigate theories in this manner, so long as you're only interested in the perturbative behavior of your model. This is a reasonable assumption, because the concordance model of cosmology gives a great fit to current observational data. My current work in dark energy focuses on investigating the perturbative behavior of dark energy from a theoretical perspective.

Dark Energy or Modified Gravity? An Effective Field Theory Approach
Jolyon Bloomfield, Éanna É. Flanagan, Minjoon Park and Scott Watson
arXiv:1211.7054 (2012)
Submitted to Journal of Cosmology and Astroparticle Physics 
A Simplified Approach to General ScalarTensor Theories
Jolyon Bloomfield
arXiv:1304.6712 (2013)
At the end of the day, what we would really like to do is to constrain our models by comparing them to observational data. My collaborators have worked on what constraints are available from the background evolution of the cosmology. However, more discriminating power should be available from analysing perturbative phenomena, such as large scale structure and baryon acoustic oscillations. To this end, we are trying to understand what effect these general theories have on large scale perturbations, and are currently working to constrain our models by comparing to observations.