TXT e-Tech, a company of the TXT Group, is looking for a candidate for a Master's thesis focused on the research, design, implementation and validation of swarming, formation and multi-agent coordination algorithms within a proprietary product.
Sebbene l'esperienza professionale e le qualifiche siano fondamentali per questo ruolo, si assicuri di verificare di possedere le soft skill preferenziali, se richieste, prima di candidarsi.
The project is part of TXT's modular cloud-based platform for the simulation of unmanned systems (UAV, UGV, USV, eVTOL), which integrates the entire UxV operational lifecycle: mission design, planning, real-time simulation (C++ core), and KPI-based debriefing within a single environment.
The candidate will contribute to the evolution of the Autonomy & Guidance Layer and the Swarming & Teaming Behaviour Engine (currently TRL 3), working on:
Formation control (leader–follower, virtual structure)Decentralized swarming based on swarm intelligenceCooperative task allocation for heterogeneous fleets
Main responsibilities
Literature review on state‐of‐the‐art formation, swarming and coordination algorithms for UxV systemsAlgorithm design and formalisation with attention to computational efficiency and real‐time constraintsImplementation of selected algorithms as software modules compatible with a C++ simulation core and microservices architectureSimulation‐based validation within a structured environment (scenario design, test campaigns, KPI evaluation)Documentation and thesis write‐up including analysis of results, limitations and future development directions
Required technical skills
Fundamentals of control theory and/or multi‐agent systemsProgramming in C++Programming in PythonFamiliarity with simulation environments (e.g. Gazebo, MATLAB/Simulink)Understanding of swarm intelligence or formation control principles
Nice to have
Experience with multi‐robot coordination or distributed algorithmsMulti‐agent reinforcement learningKnowledge of MAVLink, ROS/ROS2 or drone communication protocolsFamiliarity with HLA/DIS standards for distributed simulationOptimisation techniques (genetic algorithms, metaheuristics, gradient‐free methods)Previous exposure to aerospace or defence simulation environments
Education
Bachelor's or Master's degree in Aerospace Engineering, Robotics, Computer Science, Control Engineering, Automation or related disciplines.
Soft skills
Analytical thinking and problem‐solvingAutonomy and organisational skillsIntellectual curiosity and research aptitudeTeam collaborationClear written and oral communicationResults orientation
Ideal profile
Master's student in Aerospace Engineering or Robotics with academic experience (project or coursework) in multi‐agent systems, distributed control or swarm intelligence, and practical programming skills in C++/Python within simulation environments.
Why Choose TXT?
Career opportunities in a rapidly growing and profoundly changing company with young, international staff;Training on business‐related topics;Corporate Benefits (Ticket Restaurant, discounts as a group employee).Teamworking: Opportunity to collaborate with highly talented and passionate people in a highly professional development process;Hybrid work mode. xivgfpx
Position is open to all applicants regardless of gender, in accordance with Italian Legislative Decree 198/2006. The company promotes equal opportunities and values diversity in all its forms.