The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational Materials Science, Characterisation Materials Science, Defence Composite Materials, Functional Composite Materials, Energy, Nanomaterials, Low Dimensional Materials, Biomaterials Materials, Biological Materials, Bioinspired Materials and Sustainable Materials.
Key Job Purpose:
The current state of quantum computing is in the era of NISQ (Noisy Intermediate-Scale Quantum). The qubits experience substantial noise, allowing only specific algorithms with relatively shallow quantum circuits to be executed. In the NISQ era, hybrid algorithms run partially on quantum computers and partially on classical computers. The Variational Quantum Eigensolver (VQE) is one such optimization algorithm that helps determine the total energy of molecules. In the NISQ era, simulating molecules with more than 16 qubits is a hard problem. Therefore, it is crucial to conduct benchmarking for the quantum device, ansatz (quantum circuit), active space for ADAPT-VQE, and classical optimizer to implement VQE to calculate the total energy for a specific molecule. We are looking for a research fellow to optimize the use of the VQE algorithm for accelerating the optimization process of ground state energy calculation of molecules by leveraging selection of the quantum device, ansatz selection, active-space optimization and classical optimizer, which is very important for quantum chemistry applications, especially for specific molecular optimization problems. Our results will provide an explicit protocol for optimizing the VQE to calculate the total energy of molecules using quantum computers.
One Research Fellow (RF) position is open in Li's group led by Assoc Prof Li Shuzhou, at the School of Materials Science and Engineering (MSE), Nanyang Technological University (NTU), Singapore. Using deep knowledge of quantum physics and mathematics behind quantum computing, the candidate will work on benchmarking of ansatz selection and classical optimizer of Variational Quantum Eigensolver (VQE) using quantum computing simulator both with noise and noiseless to optimize the use of VQE for ground state energy calculation of molecules. Fellows will investigate the ansatz selection (hardware efficient ansatz and chemically inspired ansatz) combined with suitable classical optimizers which are resilient to noise.
Key Responsibilities:
- Performing research on quantum computing for chemistry, particularly benchmarking ansatz and classical optimizer of quantum algorithm (VQE) for efficient molecular simulations
- Responsible for reporting key research results and publishing scientific results in peer-reviewed journals in a timely manner
- Disseminate results to the scientific community
Job Requirements:
- PhD in chemistry, physics, material science, computer science or an allied field
- Experience with quantum computing frameworks, specifically Pennylane and Qiskit
- Experience with Variational Quantum Eigensolver (VQE) algorithms
- Proficiency in data analysis and visualization using Python libraries
- Ability to work independently and collaboratively
We regret to inform that only shortlisted candidates will be notified.
Hiring Institution: NTU
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