Machine Learning Engineer

This position is oriented towards a three-year doctoral thesis on Quantum Machine Learning for Cybersecurity, structured across three progressively advanced research stages. In an initial stage, the candidate will work on quantum software engineering methods applied to the protection of critical systems, within an international research consortium, building foundational competences in secure quantum computing architectures and threat modelling. In a second stage, starting approximately one year into the contract, the research will extend into an international project applying quantum computing to critical infrastructure operations, with the candidate’s contribution specifically targeting the cybersecurity dimension: quantum-enhanced techniques for anomaly detection, secure communications, and resilience against cyber threats. In a third and most advanced stage, in collaboration with an industrial technology partner, the thesis will apply tensor-network-based quantum-inspired machine learning to large-scale threat detection and cybersecurity analytics, transferring and scaling the security-oriented methods developed in the earlier stages to industrial-grade adversarial and anomaly-detection problems. Across all three stages, the research is designed to build towards a single central question: how quantum and quantum-inspired machine learning can improve the detection, prevention and resilience of systems against cyber threats. Title of the project to be incorporated JANUS - JUMPSTARTING AIR NAVIGATION SERVICES WITH QUANTUM SOLUTIONS PI and/or project manager Prof. Juan José Gude Prego Endowment of the contract €28,612.65 gross per year for 3 years Funding Entity Programme: Horizon Europe - Framework Programme for Research and Innovation (2021-2027) Funding entity: European Commission - SESAR 3 Joint Undertaking (JU) Contact information: ayudas.fpi@deusto.es, + Fill out the online application form and attach the following documents: a. Official academic transcripts of previous official university studies (Bachelor’s and Master’s studies), even if they are currently being taken, issued by the corresponding unit. Both academic certificates/transcripts must state the name of the degree programme, the subjects that make up the course syllabus, the subjects passed, the grades obtained and the overall GPA.

1. Master’s in Artificial Intelligence
2. Enrollment or Admissions letter for the 2026/2027 academic year in the Engineering for the Information Society and Sustainable Development PhD programme Experience required: Solid background in software engineering applied to quantum computing is required, together with familiarity with quantum algorithms, quantum programming frameworks, and machine learning methods applied to security problems (e.g., anomaly detection, intrusion detection, adversarial robustness). Prior experience in quantum security-related projects is highly valued. Working knowledge of critical-infrastructure systems is an asset for the second stage. Exposure to tensor networks and quantum-inspired machine learning methods is an asset for the later industrial collaboration stage. Strong programming skills, analytical rigor, and the ability to produce technical reports and communicate results to the scientific community are essential.

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