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Staff Mathematician - Data Analysis and Machine Learning

Date: Jun 11, 2021

Location: Oak Ridge, TN, US, 37830

Company: Oak Ridge National Laboratory

Requisition Id 6004 

Overview:

The Data Analysis and Machine Learning (DAML) Group is seeking an exceptional mathematician to work on the development of rigorous theory and algorithms for applying data analysis (DA) and machine learning (ML) techniques, customized to large-scale scientific application interests of the Department of Energy (DOE).  In particular, the application of DA and ML to scientific discovery will require an entirely new focus on algorithmic development and mathematical rigor, than what has been produced by the commercial sector.  The application of DA and ML to problems of interest to the DOE, or for scientific discovery, must leverage the large body of high performance algorithmic development with mathematics driving advances in the following major thrusts of research: 


(1) design data reduction methods for streaming scientific data that incorporate physics into compression, capable of utilizing high performance and edge computing.

(2) formulate novel mathematical tasks which are achievable given the type (plentiful or sparse) and form (labeled or unlabeled, static or online, deterministic or noisy) of observational data; 
(3) design of architectures/models which accurately capture the complexities of the data, with robust estimates of confidence in predictions and compressed quantities of interest on defined domains; 
(4) fast and scalable algorithms to fit the proposed models to data, with a theory that explains the convergence and success of these techniques; and 
(45) detailed re-analysis of the performance of the trained models to determine underlying processes that govern the given data. 

 

This particular position focuses on the potential for the use and development of tools from the mathematical sciences, as opposed to traditional statistical theory or engineering tools, to support and advance the understanding of DA and ML technology, and to accelerate algorithmic performance on leadership computing platforms. 

 

Major Duties and Responsibilities:

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

 

Specific responsibilities include:

  • Participating in the development of innovative theoretical analysis and computational methodologies for data analysis and/or machine learning technologies, customized to large-scale scientific applications, including: additive manufacturing; quantum material design; scientific imaging for material discovery; medical and tomographic imaging; population and evolutionary dynamics; cyber security and power grid analysis; consumer behavior and market analysis; as well as uncertainty quantification for engineered systems.
  • Collaboration with experts from various scientific disciplines and applications, and following team planning, goals and quality processes.
  • Authoring peer reviewed papers, technical papers, reports and proposals.
  • Maintaining memberships in professional, academic, and research organizations.

 

ORNL Ethics and Conduct:

As a member of the ORNL scientific community, you will be expected to commit to ORNL's Research Code of Conduct. Our full code of conduct, and a statement by the Lab Director's office can be found here:  https://www.ornl.gov/content/research-integrity

 

Basic Qualifications:

  • Ph.D. in Mathematics, Engineering, Data/Computational Science, or a field relevant to the job duties mentioned.
  • 2+ years of relevant research experience outside of Ph.D.

 

Preferred Qualifications:

  • Strong theoretical background in: constructive approximation; functional, complex, and real analysis; statistics; as well as numerical analysis and approximation of partial differential equations.
  • Expertise in deep learning and reinforced learning; graphical/network models; kernel methods; sparse grid methods; compressed sensing, data reduction, thresholding, and greedy approaches; stochastic optimization; as well as convex and non-convex regularizations.
  • Demonstrated experience in the design and implementation of numerical algorithms in one or more high-level computing languages within a team environment.
  • Ability to program in Python and knowledge of Machine Learning/Deep Learning frameworks, such as TensorFlow, PyTorch, etc.
  • Effective interpersonal skills. 
  • Demonstrated written and oral communication skills.

 

Questions:

Contact Rick Archibald (archibaldrk@ornl.gov). Please reference the position title and number when corresponding about this position.

 

ORNL Ethics and Conduct:

As a member of the ORNL scientific community, you will be expected to commit to ORNL's Research Code of Conduct. Our full code of conduct, and a statement by the Lab Director's office can be found here:  https://www.ornl.gov/content/research-integrity

 

Benefits at ORNL:  

UT Battelle offers an exceptional benefits package to include matching 401K, Pension Plan, Paid Vacation and Medical / Dental plan. Onsite amenities include Credit Union, Medical Clinic and free Fitness facilities.   

 

Relocation:  

UT Battelle offers a wide range of relocation benefits for individuals and families to make it easier to come and work here. If you are invited to interview, please ask your Recruiter about relocating with ORNL. 

 

 
 

 

 

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.


If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.


ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.


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