Quantum/Hybrid Algorithm Postdoctoral Scholar - 96804
Division: AM-Applied Mathematics and Computational Research

Lawrence Berkeley National Lab’s (LBNL, https://www.lbl.gov/) Applied Mathematics and Computational Research Division and the National Energy Research Scientific Computing Center (NERSC, https://crd.lbl.gov/divisions/amcr/applied-mathematics-dept/) have a joint opening for a Quantum/Hybrid Algorithm Postdoctoral Scholar to join the team.

In this exciting role, you will participate in an interdisciplinary quantum computing project. The project involves quantum and hybrid quantum-classical algorithms on NISQ-era superconducting quantum computers. As a quantum algorithms researcher, you will work closely with researchers at NERSC and quantum computing experimentalists at the Advanced Quantum Testbed on co-design of algorithms and experimental systems.

What You Will Do:

• Develop quantum and hybrid algorithms and work with experimentalists to execute algorithms on existing and near-term NISQ-era superconducting quantum computers.
  
• Benchmark the performance of quantum and hybrid algorithms, and use this data to improve efficiency.
  
• Work closely with experimentalists and FPGA engineers to understand limitations of existing hardware, and potentially participate in co-design of novel hardware/firmware features to enable next generation quantum and hybrid algorithms.
  
• Work in a multidisciplinary team environment including theorists, experimentalists, and engineers from different technical areas.
  
• Publish research findings in conferences and journals.

What is Required:

• Ph.D. in Chemistry, Physics, Computer Science, Engineering, or related fields.
  
• Strong background in quantum algorithms and computing.
  
• Experience with quantum computing software stack.
  
• Excellent communication skills to facilitate interdisciplinary work with multiple collaborators and to represent the team's work at conferences.

Desired Qualifications:

• Experience with, and understanding of, benchmarking tools and other QCVV.
  
• Prior experience with execution of quantum and hybrid algorithms (including VQE and other variational algorithms) on NISQ-era hardware is strongly desirable.
  
• Prior experience with ML and quantum machine learning.
  
• Experience with machine learning libraries such as TensorFlow, Keras, Scikit-learn, etc.
  
• Strong publication record.

The posting shall remain open until the position is filled, however for full consideration, please apply by close of business on September 20, 2022.

Notes:

• This is a full-time 1 year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
  
• This position is represented by a union for collective bargaining purposes.
  
• Salary will be predetermined based on postdoctoral step rates.
  
• This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
  
• Work may be performed on-site, hybrid, full-time telework or remote modes. Work must be performed within the United States.

How To Apply
Apply directly online at http://50.73.55.13/counter.php?id=238442 and follow the on-line instructions to complete the application process.

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Equal Opportunity and IDEA Information Links:
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