Oak Ridge National Laboratory, Mathematics in Computation Section

Position ID: ORNL-PDAA1 [#17838, 6079]
Position Title: Postdoctoral Research Associate - Multiscale Methods
Position Type: Postdoctoral
Position Location: Oak Ridge, Tennessee 37831, United States [map]
Application Deadline: (posted 2021/06/28, listed until 2021/12/28)
Position Description:    

Overview:

Subject to budget considerations, the Multiscale Methods (MM) Group at Oak Ridge National Laboratory (ORNL) is seeking a qualified applicant for postdoctoral positions in several research areas, including multiscale modeling and simulations, physics-based and data-driven model reduction, iterative solvers, scalable algorithms (including mathematical software), uncertainty quantification, and optimization.

The MM group is responsible for the design and development of basic numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation Science of the Computer Science and Mathematics (CSM) division. CSM delivers fundamental and applied research capabilities in a wide range of areas, including applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and visualization technologies, programming systems and environments, and system science and engineering.

Major Duties and Responsibilities:

The position requires collaboration within a multi-disciplinary research environment consisting of mathematicians, computational and computer scientists, and domain scientists conducting basic and applied research in support of the Laboratory’s mission.

Specific responsibilities include:

Participation in the development and analysis of new computational methodologies for scientific problems, often customized to complex and large-scale scientific applications. Delivery and support of mathematical technologies for various scientific disciplines and applications. Dissemination of research through peer-reviewed papers and technical reports, as well as seminar and conference presentations. Active participation in professional organizations. Basic Qualifications:

A Ph.D. in Mathematics, Applied Mathematics, Computational Science, or a related field completed within the last 5 years Demonstrated written and oral communication skills. Effective interpersonal skills. Preferred Qualifications:

Background in numerical analysis and methods development for differential and integral equations. Background in linear algebra and/or iterative solvers. Expertise in multiscale problems and model reduction. Experience developing mathematical tools for engineering or science applications. Experience in the design and implementation of scalable numerical algorithms on HPC architectures and within a team environment. Experience working with modern machine learning software tools and frameworks. Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.

Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details.

For more information about our benefits, working here, and living here, visit the “About” tab at jobs.ornl.gov.

Apply Here: Overview:

Subject to budget considerations, the Multiscale Methods (MM) Group at Oak Ridge National Laboratory (ORNL) is seeking a qualified applicant for postdoctoral positions in several research areas, including multiscale modeling and simulations, physics-based and data-driven model reduction, iterative solvers, scalable algorithms (including mathematical software), uncertainty quantification, and optimization.

The MM group is responsible for the design and development of basic numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation Science of the Computer Science and Mathematics (CSM) division. CSM delivers fundamental and applied research capabilities in a wide range of areas, including applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and visualization technologies, programming systems and environments, and system science and engineering.

Major Duties and Responsibilities:

The position requires collaboration within a multi-disciplinary research environment consisting of mathematicians, computational and computer scientists, and domain scientists conducting basic and applied research in support of the Laboratory’s mission.

Specific responsibilities include:

Participation in the development and analysis of new computational methodologies for scientific problems, often customized to complex and large-scale scientific applications. Delivery and support of mathematical technologies for various scientific disciplines and applications. Dissemination of research through peer-reviewed papers and technical reports, as well as seminar and conference presentations. Active participation in professional organizations. Basic Qualifications:

A Ph.D. in Mathematics, Applied Mathematics, Computational Science, or a related field completed within the last 5 years Demonstrated written and oral communication skills. Effective interpersonal skills. Preferred Qualifications:

Background in numerical analysis and methods development for differential and integral equations. Background in linear algebra and/or iterative solvers. Expertise in multiscale problems and model reduction. Experience developing mathematical tools for engineering or science applications. Experience in the design and implementation of scalable numerical algorithms on HPC architectures and within a team environment. Experience working with modern machine learning software tools and frameworks. Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.

Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details.

For more information about our benefits, working here, and living here, visit the “About” tab at jobs.ornl.gov.

Apply Here: https://career-hcm20.ns2cloud.com/sfcareer/jobreqcareer?jobId=6079&company=utbattelleP

Please note that we only use Mathjobs.org for advertisement purposes.  In order to be considered for any of our positions, all applicants MUST apply through the ORNL applicant tracking system. Please contact Kate Carter, Talent Acquisition Partner carterka@ornl.gov with any further questions regarding the application process.


Application Materials Required:
Submit the following items online at this website to complete your application:
And anything else requested in the position description.

Further Info:
https://career-hcm20.ns2cloud.com/sfcareer/jobreqcareer?jobId=6079&company=utbattelleP
 
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