Natural and man-made disasters have often consequences on service availability in a wireless access network, provoking a progressively degraded performance or even the lack of connectivity. However, given the growing importance of situation awareness, telehealth, and advanced rescue teams coordination services for the affected population, it is key to restore these services in a timely fashion, while guaranteeing the required QoS levels. To this end, UAV-mounted base stations have been recently proposed as a key instrument to achieve this goal. Nonetheless, this gives rise to the key issue of how to deploy them in a resource efficient manner, in a post-disaster context typically characterized by lack of infrastructure support and of power supply. In this work, we tackle the issue of how to jointly optimize drones deployment and user association in a QOS aware manner to efficiently cater for coverage holes and QoS degradation in a cellular network after a disaster. We formulate a network optimization problem, and we provide a two-step genetic algorithm which iteratively tunes UAV position, base station transmit power and user association in order to minimize the number of employed drones. Initial results on a realistic measurement based scenario show that our approach is able to effectively minimize the number of deployed drones while achieving a target minimum QoS.