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.

Interested in machine learning (ML) for molecular modelling? This PhD project will develop machine learning inter-atomic potentials (MLIPs) for molecular materials and organic-inorganic interfaces relevant to energy storage technology and medicinal applications.

We are seeking to recruit two highly motivated and enthusiastic Research Associates/Fellows at the University of Nottingham to perform computational research and provide support on the planning and management of projects aimed at developing novel metal hydrides and metal complex hydrides for energy storage applications in the frame of a five year Leverhulme International Professorship.

You develop and apply computational biology and machine learning tools to generate insights and hypotheses from high-dimensional molecular datasets

Implement and compare different methods for calculating binding free energy differences of ligands bound to target proteins. These methods and protocols will be applied on one class of protein targets with many crystal structures and inhibition data.

Come join a creative and collaborative team of scientists at Alltrna dedicated to leveraging emerging insights in RNA biology to develop a novel class of human therapeutics. In this role you will influence chemistry design by applying state-of-the-art computational chemistry approaches to ultimately find treatments for patients with unmet medical needs.

We are currently looking for three Computational Scientists to join our group. The successful applicants will join a rapidly growing initiative aimed at transforming research performed at large experimental Facilities (synchrotrons, neutron and muon sources, laser-based facilities etc) through a multi-disciplinary approach to data processing, computer simulation and data analytics. This initiative will provide computing hardware, build software and provide computational and data analytics expertise that will spark a paradigm shift in the capability of scientists to design, analyse and interpret experiments.

Are you interested in astrochemistry, computational methods and machine learning? In the respective groups of Assoc. Prof. Mie Andersen and Prof. Bjørk Hammer at Department of Physics and Astronomy and Center for Interstellar Catalysis, Aarhus University, we have an open post-doctoral position within these research topics. Applications should cover aspects relevant to interstellar catalysis and grain surface chemistry.