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Up Directory CCL 19.12.02 Postdoctoral Research Associate in Computational Chemical and Materials Sciences, Oak Ridge, TN
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Date: Mon Dec 2 16:57:39 2019
Subject: 19.12.02 Postdoctoral Research Associate in Computational Chemical and Materials Sciences, Oak Ridge, TN
Under the supervision of Prof. Stephan Irle, the successful candidate will conduct advanced
atomic-scale simulations of complex systems through approximate quantum chemical methods
in combination with machine learning corrections on exascale computing platforms.  The Fluid
Interface Reactions, Structures and Transport (FIRST) Energy Frontier Research Center is funded
by the U.S. Department of Energy (DOE), Basic Energy Sciences (BES) program.  This position
resides in the Computational Chemicals and Materials Group in the Computational Sciences and
Engineering Division (CSED), Computing and Computational Sciences Directorate (CCSD) and
the Chemical Sciences Division (CSD), Physical Sciences Directorate (PSD) at Oak Ridge National
Laboratory (ORNL).   

The goal of the FIRST Center is to achieve a fundamental understanding and validated, predictive
models of the atomistic origins of electrolyte and coupled electron transport under
nanoconfinement that will enable transformative advances in capacitive electrical energy storage
and other energy-relevant interfacial systems.  As part of our research team, you will be involved in
the development and application of near-linear scaling implementations of the density-functional
tight-binding (DFTB) method on hybrid CPU/GPU architectures such as Summit within the
frameworks of the DFTB+ and GAMESS-US codes.  Bias-correction will be performed via neural
networks trained at high-level data.  The methodology will be applied to the study of ion diffusion
in aqueous media under confinement and redox reactions on supercapacitor electrode surfaces.
Our studies bridge the system size and simulation time gap between first principles Born-
Oppenheimer molecular dynamics simulations and large-scale reactive force field simulations. 
The project offers an opportunity to enhance the accuracy of DFTB potentials on the one hand, and
the accuracy of reactive force fields on the other.  The insights gained from such multiscale
simulations will guide experimental efforts in the development of supercapacitor systems capable
of efficient ion and electron transport to achieve simultaneous high pseudocapacitive power and
energy density, revolutionizing the energy economy landscape of the future.

	Implement efficient parallel eigensolver algorithms on massively parallel supercomputer
          systems via GPU/CPU hybrid programming models based on MPI and MAGMA libraries as well
          as ELSI/ELPA
	Perform simulations of ion diffusion/electron transport and redox reactions in aqueous
           solutions under confinement in supercapacitor electrodes
	Scale up currently existing neural network correction tools based on TensorFlow and create
          efficient interfaces for on-the-fly corrected DFTB/MD simulations
	Develop and apply these methodologies in close collaboration with the experimental and
          theoretical groups at the Center
	Take advantage of leadership class high performance computing facilities available at ORNL
           and NERSC
	Conduct research and report results in open literature journals, technical reports, and at
          relevant conferences

	A PhD in Theoretical Chemistry, Molecular/Solid State Physics, or a related discipline completed
          within the last five years 
	Programming and experience in major quantum chemistry codes and parallel programming
	Demonstrated experience in first-principles simulations of systems under consideration of
          periodic boundary conditions

	Experience with Born-Oppenheimer molecular dynamics simulations and/or free energy free
          energy perturbation and other methods of quantifying thermodynamics in silico
	An excellent record of productive and creative research as demonstrated by publications in
          peer-reviewed journals 
	Excellent written and oral communication skills and the ability to communicate in English to a
          scientific audience
	Motivated self-starter with the ability to work independently and to participate creatively in
          collaborative and frequently interacting teams of researchers  
	Ability to function well in a fast-paced research environment, set priorities to accomplish
          multiple tasks within deadlines, and adapt to ever changing needs 

The appointment length will be up to 24 months with the potential for extension. Initial appointments
and extensions are subject to performance and availability of funding.

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.
Please provide a list of publications and a complete formal transcript of Ph.D. coursework when applying for this position. Three letters of reference are required and can be uploaded to your profile or emailed directly to ORNLRecruiting-$  Please include the title of the position in the subject line.
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Modified: Mon Dec 2 21:57:39 2019 GMT
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