Postdoctoral Fellow

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Position Summary:

Florida Atlantic University is seeking a Postdoctoral Fellow with broad expertise in the Application of Machine Learning Based Data Compression and Analytics. This is a 12-month, non-tenure position with potential for a 2nd year extension based on availability of funds and performance.

We are developing a data compression and management tool to address the bottlenecks in output, storage, access, and analysis of large scientific datasets. The underlying algorithm in this tool uses machine learning to learn a set of features from a small amount of representative solution data. These features are then used within a computational mechanics framework to generate ‘lossy’ but highly reduced representations of the original high-fidelity solution data. The current work is focused on: 1) scaling this tool to massively parallel systems, such as the Frontier and Aurora exascale computers, 2) improving the machine learning algorithms for feature extraction, 3) introducing support for unstructured grids, and 4) establishing the error bounds in the physical metrics of interest.

The Postdoctoral Fellow will :

• work closely with the industry collaborator to develop relevant algorithm and code
• communicate the progress in scientific & project reports, at scientific conferences, and in peer-reviewed journal publications
• support training of junior researchers in the group
• learn the latest machine learning techniques and use them to optimize the algorithm and code

The College of Engineering and Computer Science at Florida Atlantic University seeks scholars who are committed to supporting the learning needs of students from diverse backgrounds and to thoughtfully engaging all communities in higher education. Florida Atlantic University embodies a culture of strategic and collaborative community engagement that results in mutual benefit to the institution and the various internal and external communities that it serves.

Minimum Qualifications:

Minimum qualifications:
• A doctorate (foreign equivalent acceptable) in computer science, applied mathematics, engineering, or related field
• Good understanding of computational linear algebra and applied mathematics
• Good understanding of C++ programming
• Familiarity with high performance computing
• Ability to work independently as well as to collaborate in a team environment
• Interest in machine learning
Preferred experience:
• Excellent C++ programming skills with past experience in contributing to a medium to large codebase
• Experience with developing highly scalable high-performance computing software
• Experience with CFD (or other) solver development on unstructured grids
• Past experience with developing finite element solvers
• Experience with neural network models

Salary:

$55,000 - $65,000

College or Department:

College of Engineering and Computer Science

Location:

Dania Beach

Work Days and Hours:

N/A

Application Deadline:

2024-02-29

Special Instructions to Applicant:

This position is open until filled and may close without prior notice.
This position is subject to funding.
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: (i) a cover letter, (ii) curriculum vitae, and (iii) 2 letters of reference/recommendation.
In the event that individuals writing letters of reference/recommendation want their letters to remain confidential, letters may be emailed to Dr. Rohit Deshmukh at [email protected].
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:
Selected candidates must successfully complete and pass all employment screenings prior to the start of employment. Employment screenings may include a criminal background check (level I and level II), motor vehicle check, credit check, reference checks, alcohol, and drug screening check.
Accommodations:
Individuals requiring accommodation, please call 561-297-3057. 711