Position overview
Position title: Postdoctoral Scholar
Salary range: See Table 23 for the salary range for this position. A reasonable estimate for this position is $69,073 - $82,836
Percent time: 2 years
Anticipated start: January 1, 2026
Application Window
Open date: October 7, 2025
Next review date: Sunday, Nov 30, 2025 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee.
Final date: Saturday, Oct 3, 2026 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
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 https://larsson-research.de/.
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.
Application Requirements
Document requirements
- Curriculum Vitae - Your most recently updated C.V.
- Cover Letter
- Authorization to Release Information Form - As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.
"Misconduct" means any violation of the policies or laws governing conduct at the applicant’s previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer.
Required Authorization of Information Release may be found here. Please complete, sign, and upload the required Authorization of Information Release to your application. - Examples of programming code, link to source code repository, or description of created properietary code (Optional)
Reference requirements
- 3 required (contact information only)
Apply link: https://aprecruit.ucmerced.edu/JPF02034
Help contact: [contact details available in the full listing]
