Quantum algorithms process information stored in qubits, the basic memory unit of quantum processors, and quantum operations (called gates) are the building blocks of quantum algorithms. In order to be run on quantum computing hardware, quantum algorithms must be compiled into a set of elementary machine instructions (i.e., quantum gates). Since currently available quantum circuits suffer a number of technological problems such as noise and decoherence, it is important that the process that carries out the quantum computation be somehow adapted to the physical limitations of the quantum hardware of interest, by means of a proper compilation. For practical applications, it is important to make quantum computation able to tackle problem instances of more and more realistic size. To this aim, the ability to quickly compile quantum algorithms of good quality is paramount. This project aimed at investigating the application of novel AI-based meta-heuristics to the problem of compiling quantum circuits to emerging quantum hardware, particularly focusing on Space-related applications. The initial modelling efforts was focused studying the so-called Quantum Alternate Operator Ansatz (QAOA) algorithms on the gate-model noisy intermediate-scale quantum (NISQ) processor units. This approach intends to improve over the compilation algorithms applied to the current quantum computing software development kits (e.g., [Qiskit 2021]), devise solutions that are easily adaptable to different classes of problems.