We are seeking a Postdoctoral Research Associate who will support the Advanced Computing for Chemistry and Materials in the National Center for Computational Sciences (NCCS), Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL) to perform leading-edge computational materials research and development.

The project focuses on the computational study of the effects of pressure on the Woodward-Hoffmann rules, organocatalysis, tunnelling, and nanothread formation mechanism. The candidate will work on computing potential energy surfaces of organic reactions under pressure using the eXtreme Pressure-Polarizable Continuum Model (XP-PCM) method.

We are seeking to appoint a Lecturer, Senior Lecturer or Reader in Computational Chemistry, as part of our ongoing investment and expansion in research excellence. You will be expected to develop an innovative teaching and research portfolio in Computational Chemistry, publishing world-class research that will lead to a successful externally funded research program supporting postdoctoral research staff and PhD students, and establishing links with industry.

The project focuses on the computational study of the effects of pressure on the Woodward-Hoffmann rules, organocatalysis, tunnelling, and nanothread formation mechanism. The candidate will work on computing potential energy surfaces of organic reactions under pressure using the eXtreme Pressure-Polarizable Continuum Model (XP-PCM) method.

A background in theory underlying computational investigations: molecular-mechanics/quantum-mechanics/thermochemistry is desired.

Our company is seeking a creative, self-motivated computational chemist with exceptional interpersonal and problem-solving skills to join the Modeling group in Kenilworth, NJ, part of the Computational and Structural Chemistry (CSC) department. We are looking to expand our capability in peptide computational chemistry to support our future peptide strategy.

The AFRL Materials and Manufacturing Directorate seeks to hire a motivated and experienced engineer or scientist to conduct computational polymer physics research & development in the Polymers & Specialty Materials Branch of the Photonic, Electronics, and Soft Materials Division.

Let’s do this. Let’s change the world. During this program, you will develop machine learning-based tools for efficient conformational sampling of both small molecules and protein-ligand complexes. You will also have the opportunity to apply the tools you develop to drive drug discovery projects, by providing fast and accurate estimates of protein-ligand binding free energies.

The Butler University College of Pharmacy and Health Sciences seeks a collegial, dynamic faculty member to provide innovative teaching and conduct productive research in a tenure-track Assistant Professor position in the Department of Pharmaceutical Sciences.

The Vir Small Molecule Discovery group is looking for an experienced scientist to become the foundational hire of our small molecule molecular modeling group. You will collaborate in interdisciplinary discovery teams to help invent new small molecule and bioconjugate medicines. Informatics and modeling techniques will be used to accelerate lead identification and lead optimization activities. You will also take on mentoring and leadership responsibilities over time.

The Group of Physics and Chemistry of Materials in the Theoretical Division of Los Alamos National Laboratory has an immediate postdoctoral position available for a talented and motivated researcher interested in at least one of the following areas: (i) electronic structure theory calculations for design of materials for CO2 capture and electroreduction, (ii) computational vibrational spectroscopy and (iii) machine learning and data science approaches for materials science.

We are seeking a Computational Materials Scientist/Chemist to help us provide insight to the processes that define the behaviors of physical systems. As a member of our team, you will contribute to exciting projects supporting organizations such as the US Department of Defense, the National Science Foundation, and NASA.

Within an international collaboration with the Matherials-team at CERMICS/Ecole des Ponts (France), we are looking for a Ph.D. candidate or post-doc reasearch associate to run a project on a cutting-edge and interdisciplinary topic on efficient numerical methods with applications in computational chemistry.

Terray is currently seeking a motivated, creative, and experienced computational chemist. As an integral member of our Computational and Data Sciences (CDS) team, the candidate will be responsible for developing and applying state-of-the-art physics-based and machine learning approaches to accelerate the design of small molecules at all stages of the drug discovery pipeline.

Postdoc in computational materials science

The Department of Chemistry in the Faculty of Science is looking for a full-time (100%) doctoral scholarship holder in the field of Computational Chemistry

Machine learning (ML/AI) is becoming one of the most commonly used approaches for predicting biological activities of molecules based on features derived from the molecular structures. Due to its efficiency, ML/AI models are especially useful to rank order and filter enumerated libraries with hundreds of thousands of molecules.

We are seeking excellent and highly motivated MSc, Ph.D. students, and/or postdocs that are interested in pursuing state of the art interdisciplinary research in quantum computational materials.

A postdoc position is available in the group of Prof. Zhenfei Liu (https://liugroupwsu.weebly.com/) at Wayne State University (Detroit, USA). This position focuses on first-principles calculations of electronic, vibrational, magnetic, and topological properties of complex materials, including but not limited to: metal-organic frameworks, quantum dots and their assemblies, heterogeneous interfaces, low-dimensional materials, etc.

We are looking for highly motivated candidates who are proficient in computer programming and mathematical modeling. Candidates should hold the equivalent of a master degree in physics, computational chemistry, materials science, or a related discipline.