  We present a new automated cluster search algorithm, stressing its advantages
relatively to others available in the literature. Applying it to the
photometric data of the ESO Imaging Survey (EIS, Renzini & da Costa 1997)
allowed us to produce, with a high degree of confidence, a new catalogue of
cluster candidates up to z approximately equal to 1.1.
