CEDoc – UM6P – CC: Next Generation Quantum AI Algorithms Full-time

Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its fields

The University is engaged in economic and human development and puts research and innovation at the forefront of African development. A mechanism that enables it to consolidate Morocco’s frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa.

Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally.

Context:

Although AI has made rapid progress over the past decade, it has not yet overcome technological limitations. With the unique features of quantum computing, obstacles to achieving AGI (Artificial General Intelligence) can be eliminated. Quantum computing can be used for the rapid training of machine learning models and to create optimized algorithms. An optimized and stable AI provided by quantum computing can complete years of analysis in a short time and lead to advances in technology. Neuromorphic cognitive models, adaptive machine learning, or reasoning under uncertainty are some fundamental challenges of today’s AI. Quantum AI is one of the most likely solutions for next-generation AI. Researchers’ near-term realistic aim for quantum AI is to create quantum algorithms that perform better than classical algorithms and put them into practice.

Research objective:

The aim of this project is to explore and develop a set of Quantum algorithms for learning asgeneralizations of classical learning models. While the quantum computers are not yet deployed, Google’s TensorFlow Quantum (TFQ), an open-source library for quantum machine learning, is an example of a suite of tools that combines quantum modeling and machine learning techniques. The aim of TFQ is to provide the necessary tools to control and model natural or artificial quantum systems. The project will be supervised by Prof Lamiae Azizi in collaboration with the University of Melbourne (Australia) and the University of Edinburgh (UK).

Required documents:

• Transcripts of Bachelor and Masters.
• CV
• Cover letter

Admission Criteria:

Mandatory:

– Knowledge of modern Machine Learning

– Solid Knowledge of Python

– Solid mathematical background

– Good communications skills in English

Number of positions : 1

UM6P.