  Galaxy redshift surveys are one of the pillars of the current standard
cosmological model and remain a key tool in the experimental effort to
understand the origin of cosmic acceleration. To this end, the next generation
of surveys aim at achieving sub-percent precision in the measurement of the
equation of state of dark energy $w(z)$ and the growth rate of structure
$f(z)$. This however requires comparable control over systematic errors,
stressing the need for improved modelling methods. In this contribution we
review at the introductory level some highlights of the work done in this
direction by the {\it Darklight} project. Supported by an ERC Advanced Grant,
{\it Darklight} developed novel techniques for clustering analysis, which were
tested through numerical simulations before being finally applied to galaxy
data as in particular those of the recently completed VIPERS redshift survey.
We focus in particular on: (a) advances on estimating the growth rate of
structure from redshift-space distortions; (b) parameter estimation through
global Bayesian reconstruction of the density field from survey data; (c)
impact of massive neutrinos on large-scale structure measurements. Overall,
{\it Darklight} has contributed to paving the way for forthcoming
high-precision experiments, such as {\it Euclid}, the next ESA cosmological
mission.
