Job Description: The role of this position will focus on several aspects of high-dimensional data (tensor) analysis. The research will develop computational techniques to efficiently process multiway arrays, with a focus on applications to oceanographic and atmospheric data. The research also has theoretical components, to analyze the performance of the proposed numerical approaches.

The research contributes to the project “Tensor Analysis, Maximum Likelihood Estimation, and Sampling” (TAMaLES), which seeks to develop novel theoretical insight to identify the best low-rank tensor models that can be computed for given high-dimensional data sets. The work focuses on tensor decompositions with the goal of deriving low-rank tensor recovery error bounds that are informative in practice. TAMaLES is part of an ongoing collaboration with Sandia National Laboratories, funded by the US. Department of Energy. The appointed researcher is expected to communicate frequently with a team of Sandia researchers.

Applications to the oceanographic and atmospheric sciences will also be considered. The goal of this component of the research is to investigate the advantages of multi-dimensional signal processing, in contrast to standard 1D and 2D methods. Tensor decomposition-based techniques will be developed to efficiently process hyperspectral images, holography data, seismic volumes, single-photon count data, and underwater lidar volumes.

Minimum Qualifications:

- A Ph.D. in mathematics, applied mathematics, computer science, electrical engineering, or a related area is required.

- Research experience in at least one of the following areas: tensor decompositions, multiway data analysis, compressive sensing, low-rank matrix/tensor recovery, random matrix\tensor theory, signal processing, computational imaging, numerical optimization, maximum-likelihood estimation.

- Familiarity with conducting analysis of large datasets using MATLAB, Python, or other programming languages.

- Must be able to work independently, be self-motivated, well-organized, and a critical thinker.

- Good written and verbal communication skills are required.

For questions, contact Dr. Oscar Lopez (lopezo at fau.edu)

Salary: $55,000, per annum

Special Instructions to Applicant: This position is open until filled and may close without prior notice.

All applicants must apply electronically to the currently posted position on the Office of Human Resources' job website (https://fau.edu/jobs ) by completing the required employment application for this recruitment and submitting the related documents.

Required Documents: FAU’s Career Page permits the attachment of required/requested documentation. PLEASE NOTE: A maximum of five (5) documents may be attached to your application. If more than five (5) documents are required for submission, please combine additional documents into a single attachment to not exceed the maximum permitted.

The site permits the attachment of required/requested documentation. When completing the online application, please upload the following:

1. CV

2. Cover letter (one page)

3. Research statement

4. Two letters of recommendation (or contact info).

Transcripts: Final candidate will be required to have official, sealed transcripts and original NACES evaluation, if applicable, sent from their educational institution to Human Resources prior to the start of employment.

Background Screening: Successful completion of a pre-employment background check is required for the candidate selected for this position.