KIM is hiring!


The Knowledgebase of Interatomic Models (KIM) project is seeking an exceptional computational scientist for basic research and infrastructure development to shape the future of molecular simulation.

KIM is an online framework funded by the U.S. National Science Foundation that aims to make molecular simulations reliable, reproducible and portable. Interatomic models archived on are verified for coding integrity, and tested by computing their predictions for a variety of material properties. Models conforming to the KIM application programming interface (API) work seamlessly with major simulation codes that have adopted the KIM API standard. To learn more about KIM visit our Getting Started page.

The KIM project has just been renewed and is planning an ambitious program to advance the state of molecular simulations. This includes the following efforts:

  • Uncertainty quantification (UQ) for molecular simulations that accounts for the systematic uncertainty inherent in the interatomic model.

  • Rigorous selection of interatomic models for specific applications based on machine learning approaches.

  • Improving researcher workflows by leveraging KIM resources including access to archived models and precomputed material properties.

This work lies at the frontier of current developments in the science and computing of molecular simulations. It is an unusual opportunity to contribute to the state-of-the-art of the field and to interact with its leaders through the KIM organization with more than 500 members in 42 countries.

The successful candidate will be able to participate in different aspects of the project based on their interests and can also propose to lead an independent research project building on or contributing to the KIM project. Appointments will be considered at either the postdoctoral or research scientist levels depending on background and seniority. Benefits:

  • Competitive salary

  • Dynamic multifaceted research project

  • Travel support to attend conferences to represent the KIM project

  • Potential for collaboration on a variety of ongoing research projects

  • Support for up to four years

Required skills:

  • Ph.D. in physics, chemistry, materials science, mechanics, computer science or related discipline with a focus on molecular simulation of materials. (Exceptional candidates without a Ph.D. may be considered.)

  • Expert-level programming knowledge in one or more of the following languages: C, C++, Fortran, Python.

  • Expert-level software engineering skills including one or more of the following: revision control (git), shell scripting, binary packaging, continuous integration tools, unit testing, API design.

  • Excellent written and oral communication skills.

Experience in one or more of the following areas is highly-desirable:

  • Development of interatomic models (physics-based or data driven)

  • Molecular simulation frameworks (LAMMPS, ASE, DL_POLY, GULP, …)

  • First principles calculations (VASP, Quantum Espresso, Gaussian, …)

  • High-performance computing (MPI, OpenMP, CUDA, …)

  • Machine learning (multitask learning, neural networks, TensorFlow, PyTorch)

  • Web development and scientific visualization (HTML, CSS, Bootstrap, Javascript, C3, D3, …)

To apply:

Applications will be considered on an ongoing basis until the position is filled. The position is available immediately. Interested individuals are encouraged to contact Professor Ellad Tadmor at Please provide the following:

  • Cover letter describing how your background fits the above needs and requirements and what additional special skills you would bring to the KIM project.

  • CV or Resume.

  • Names and contact information for three references familiar with your work.

The position is based at the University of Minnesota Twin Cities in Minneapolis, MN, USA. The project is led by Prof. Ellad Tadmor (UMN), Prof. Ryan Elliott (UMN), Prof. George Karypis (UMN) and Prof. Mark Transtrum. This interdisciplinary team has extensive experience in molecular and multiscale simulations, mechanics of materials, advanced computing, machine learning, uncertainty estimation, differential geometry and model manifolds.

The University of Minnesota is an EEO/AA employer and educator.