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Postdoctoral Scholar in Theoretical Chemistry/Applied Mathematics (Multiple Hires). Job Opening In Merced – Now Hiring UC Merced

Postdoctoral Scholar in Theoretical Chemistry/Applied Mathematics (Multiple Hires).

    United States Jobs Expertini Expertini › United States › Jobs › Merced › Life Scientists › Postdoctoral Scholar In Theoretical Chemistry/applied Mathematics (Multiple Hires).

Job description

Position description


Applications are invited for multiple full-time postdoctoral research positions in the groups of Professor Christine Isborn (Chemistry), Harish Bhat (Applied Math), and Henrik R.

Larsson (Chemistry and Physics) at the University of California, Merced.


The postdoctoral scholars will work on a DOE-funded SciDAC project Moving Electrons through Space and Time: Enabling the Quantum Dynamics of Chirality-Induced Spin Selection Through Novel and Scalable Computational Methods.


The project involves close collaborations with teams at University of Michigan, Rutgers University Newark, and Lawrence Livermore National Laboratory.

Available computational resources include shared clusters at Merced, computing nodes dedicated to the group, and the NERSC supercomputing cluster.

Postdoctoral scholars will be expected to present and engage at national and international conferences, write journal articles, and assist with mentoring students.


Isborn group

The position will involve applying multiple time-dependent electronic structure and nonadiabatic dynamic methods to model the CISS effect in molecular systems.

Method development, potentially in the realm of time-dependent current DFT, will likely also be required as we learn about physical phenomena underlying the CISS effect.


Bhat group

The position will involve developing new mathematical/computational methods at the intersection of scientific computing and machine learning.

At a high level, the project is to build neural network models of potentials that appear in Hamiltonians for time-dependent quantum systems.

The postdoc will be expected to contribute to various aspects of this project, e.g.: (a) fusing modern neural architectures with first-principle models of time-dependent quantum systems, (b) developing bespoke adjoint methods to efficiently compute required gradients/Hessians, and (c) incorporating symmetries and constraints into neural network models.

Of particular interest are candidates who have a background and/or interest in one or more of the following: optimization and optimal control (esp.

optimal control of partial differential equations (PDE) or PDE-constrained optimization), scientific machine learning, and scientific computing (esp.

for time-dependent quantum systems).


Larsson group

The position will involve developing methods based on the density matrix renormalization group (DMRG) for real-time electron dynamics.

Applications will involve real-time dynamics of chiral molecules, and the generation of reference data for density functional inversion.

Additional applications are possible on quasi-exact nonadiabatic nuclear dynamics simulations using tensor network states (ML-MCTDH) of vibronic coupling models.

Of particular interest are candidates who have a background and/or interest in one or more of the following: Electronic structure/dynamics, tensor network states, multireference electronic structure, relativistic electronic structure.

More information about the Larsson group can be found at .





Qualifications



Basic qualifications

For positions in Chemistry/Physics: Applicants are required to have a Ph.D. in Chemistry, Physics, or a related field.

Experience with quantum simulations (broadly defined), programming (Python, Julia, C++, Fortran, etc), and excellent oral and written communication skills are required.


For positions in Applied Mathematics: Applicants are required to have a Ph.D. in Applied Mathematics, Mathematics, Control, Operations Research, Statistics, or a related field.

Experience in numerical analysis, scientific computing, and either optimization or machine learning is required.

Experience with programming (Python, NumPy/SciPy, JAX/PyTorch/TensorFlow, C++), and excellent oral and written communication skills are required.





Preferred qualifications

For positions in Chemistry/Physics: The ideal candidate has experience in developing computational methods in the fields of theoretical chemistry/physics.


For positions in Applied Mathematics: The ideal candidate has experience in machine learning and PDE-constrained optimization for time-dependent systems; the ideal candidate also has a strong interest in quantum dynamics.






Required Skill Profession

Life Scientists


  • Job Details

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