PhD Scholarship: Quantum Compiler for Transpilation

Monash University; City of Melbourne; On-site; AUD 35,000 - 47,000; Full time

Benefits offered by this job

Scholarship stipend

Candidature funding

Travel grant

Job summary

Monash University invites applications for a PhD scholarship on Quantum Compiler for Efficient Circuit Transpilation at the Clayton campus, Melbourne. The project aims to bridge quantum algorithms with hardware execution using advanced software components and reinforcement learning.

The successful candidate will join the Scalable Quantum Systems Lab, collaborating with researchers and PhD students to advance quantum computing while pursuing a Research Doctorate (PhD) for up to 3.5 years.

Qualifications

• Bachelor’s degree with four years of study including a research thesis or project; honours First Class recommended.
• Master’s degree with a research thesis or project; honours First Class recommended.
• Equivalent qualification or experience as deemed by GRC (or delegate).
• Meet university English language requirements.

Responsibilities

• Develop quantum compiler methods to bridge algorithms and execution on quantum processors.
• Create quantum software components and reinforcement learning models for transpilation of quantum circuits.
• Aim to minimise resources (qubits, gates) for quantum circuit execution.

Skills

Machine learning

Deep learning

Software programming

Python

PyTorch

Education

Bachelor’s with honours

Master’s with honours

Equivalent qualification/experience

Tools

Python

PyTorch

Job description

Monash University invites applications for a PhD scholarship on Quantum Compiler for Efficient Circuit Transpilation at the Clayton campus, Melbourne. The project aims to bridge quantum algorithms with hardware execution using advanced software components and reinforcement learning.

The successful candidate will join the Scalable Quantum Systems Lab, collaborating with researchers and PhD students to advance quantum computing while pursuing a Research Doctorate (PhD) for up to 3.5 years.