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** Cover letter required for all positions and optional for facilities, campus services, and hospitality positions unless otherwise specified. Job Description Summary
The Department of Computer Science at Wake Forest University invites applications for a postdoctoral research fellowship. The candidate will work primarily with Dr. Grey Ballard and Dr. Aditya Deverakonda to design, implement, and analyze high-performance algorithms for sparse matrix and tensor computations. We are particularly interested in scholars who have a strong background in numerical linear algebra, numerical analysis, and/or parallel and high-performance computing. The successful candidate will collaboratively prepare presentations and papers for dissemination of results and help train graduate and undergraduate student research assistants. In addition to conducting research, the fellow will have the opportunity to teach at the undergraduate level if mutually agreeable. This is a one-year contract position with possible extensions.
The fellow will be part of Sparsitute: A Mathematical Institute for Sparse Computations in Science and Engineering. Sparsitute is supported for 5 years by the Department of Energy as a Mathematical Multifaceted Integrated Capability Center (MMICC). Sparsitute is a collaboration between LBNL, ORNL, Purdue University, University of Illinois at Urbana-Champaign, Indiana University, and Wake Forest University. The postdoctoral fellow will be hosted at Wake Forest but will get a chance to collaborate closely and network with all the PIs and personnel in these 6 institutions. Job Description Essential Functions:
Required Education, Knowledge, Skills, Abilities:
- Develops algorithms and analyzes their time and accuracy
- Implements the algorithms using e.g. Python, MATLAB, C/C++, CUDA, OpenMP, and/or MPI
- Gathers experimental data to evaluate and analyze behavior
- Maintains accurate, organized, and complete records of research
- Effectively communicates results
- Writes and publishes papers in top conferences and journals
- Contributes to training of undergraduate and Master's level graduate researchers
Preferred Education, Knowledge, Skills, Abilities:
- PhD in Computer Science, Mathematics, Statistics, or a closely related field
- Strong background in numerical linear algebra, numerical analysis, or parallel and high-performance computing
- Demonstrated ability to write professional quality manuscripts, in a timely fashion
- Excellent interpersonal, communication, and time management skills
- Ability to work individually or collaboratively as part of a team
- Ability to provide a research environment that is conducive to learning
Additional Job Description
- Proficiency with parallel software development
- Experience with matrix and tensor decompositions
- Experience in teaching computer science courses
Please include the following items in order to complete your application: 1) CV, 2) a cover letterthat includes a statement of research experience and interests, and 3) 2-3 references that can provide letters of support Time Type Requirement
Full time Note to Applicant:
This position profile identifies the key responsibilities and expectations for performance. It cannot encompass all specific job tasks that an employee may be required to perform. Employees are required to follow any other job-related instructions and perform job-related duties as may be reasonably assigned by his/her supervisor.
In order to provide a safe and productive learning and living community, Wake Forest University conducts background investigations and drug screens for all final staff candidates being considered for employment.
Wa keForestseeks to recruit and retain a diverse workforce while promoting an inclusive work environment committed to excellence in the spirit of Pro Humanitate. In adherence with applicable laws and as provided by University policies, the University prohibits discrimination in its employment practices on thebasis of race, color, religion, national origin, sex, age, sexual orientation, gender identity and expression, genetic information, disability and veteran statusand encourages qualified candidates across all group demographics to apply.