We have multiple postdoc openings in quantum/classical machine learning and in uncertainty quantification.  Below is a short summary of all possible openings:

1.       Postdoc in uncertainty quantification.

Requirement: We expect the candidate to have rich experience in one or any combination of the following topics: high-dimensional uncertainty quantification, experimental design, verification of uncertainty system, control and/or optimization with various uncertainties.

Note: The postdoc will be working on theory and numerical algorithms, but he/she will be collaborating with hardware designers (e.g., photonic integrated circuit designers) to make real impact in the semiconductor industry.

2.       Postdoc in quantum artificial intelligence (AI)

Requirement: We expect the candidateto have a rich experience in quantum information processing and quantum computing. Research experience in any of the following fields will be a big plus: tensor networks, quantum machine learning, quantum SAT (satisfiability).

Notes: The postdoc will be working on the theory & algorithm part, but he/she may collaborate with quantum hardware designers and machine learning groups to solve the real problems. 

3.        Postdoc in scientific and safe/robust machine learning.

Requirement: We expect the candidate to have rich experience in one or any combination of the following topics: ODE/PDE methods for deep learning, optimal control for machine learning, robustness or safety of machine learning. Candidates with research experience in high-dimensional Hamiltonian-Jacobi-Bellman’s equations will be a big plus (but not required).

Note: The postdoc will be working with current group members, as well as collaborators from the math and computer science department.

4.       Postdoc in numerical methods for hardware-friendly big data and machine learning.

Requirement: We expect the candidate to have rich experience in numerical analysis, scientific computing or numerical optimization. Candidates with a strong background in low-precision or mixed-precision numerical methods will be a big plus.

Note: The postdoc will be working on the theory & algorithm part, but he/she may collaborate with hardware designers and our industrial partners to enable efficient hardware/software co-design of AI systems.

Interested applicants please send a CV (and possibly also representative publications) to Zheng Zhang (zhengzhang@ece.ucsb.edu).  Please indicate which position you are interested in.