Deadline for receipt of applications: February 8th, 2024 23:59 AoE (09 February 2024, 13:59h Europe/Madrid Time)
The success of classical Machine Learning / Deep Learning algorithms in the past decade has helped establish the field as one of the pillars of many modern research and industrial areas. With the increased availability of Quantum Computers came the desire to expand Machine Learning into the quantum domain, allowing models to be trained on quantum as well as classical data. This PhD is focused on developing efficient and scalable Quantum Machine Learning algorithms, with an emphasis on graph-based learning. Applications range from predictions on similarity graphs between quantum states, analysis and optimization of quantum circuits to learning on graph states and more general network analysis.
IMDEA Networks Institute aims to increase the proportion of women and therefore qualified female applicants are explicitly encouraged to apply. Until a balanced ratio of men and women has been achieved at the institute, preference will be given to women if applicants have similar qualifications. IMDEA Networks Institute actively promotes diversity and equal opportunities. Applicants are not to be discriminated against in personnel selection procedures on the grounds of gender, ethnicity, religion or ideology, age, sexual orientation (anti-discrimination). People with disabilities who have the relevant qualifications are expressly invited to apply.