# Research Scientist, Material Intelligence **Company**: Google DeepMind **Location**: London, UK **Work arrangement**: onsite **Experience**: senior **Job type**: full-time **Salary**: Not specified **Category**: Engineering **Industry**: Technology **Wikidata**: https://www.wikidata.org/wiki/Q15733006 **Apply**: https://job-boards.greenhouse.io/deepmind/jobs/7353237?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_9c2c3e84-e05 ## Description ## Snapshot Science is at the heart of everything we do at Google DeepMind. We're building better algorithms inspired by science to accelerate scientific discovery. ## The Role We're seeking an exceptional and highly motivated expert in computational materials science to help drive our in-silico discovery efforts. This is a senior position with a unique role blending scientific leadership, hands-on modeling, strategic input, and mentorship. ## Key Responsibilities: - Computational Leadership & Supervision: Lead and mentor a team of computational materials scientists, guiding project roadmaps, fostering scientific growth, and ensuring high-quality research output. - Modeling Strategy & Execution: Design and execute large-scale computational screening campaigns using DFT, molecular dynamics, and other simulation methods to predict novel materials with desired properties. - Broad Materials Expertise: Apply deep physical and chemical intuition across diverse material classes to identify promising avenues for discovery. - Method & Workflow Development: Review, integrate, and develop state-of-the-art computational tools and automated, high-throughput workflows on Google's large-scale compute infrastructure that can be tightly integrated with AI search methods. - Data Integrity & Feedback Loop: Ensure the generation of high-quality, reproducible computational data. Play a key role in structuring and curating simulation databases to train next-generation AI models. - Cross-functional Collaboration: Work closely with AI researchers and software engineers to translate AI-generated hypotheses into scalable simulation pipelines and to troubleshoot the simulation-to-reality gap. - Reporting & Communication: Clearly and efficiently report on computational progress, new material predictions, and challenges to the wider Material Intelligence team and key stakeholders. ## About You To set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience: - Significant post-PhD experience in Computational Materials Science, Solid-State Chemistry, Condensed Matter Physics, or a related field. - Proven track record of supervising and mentoring junior computational researchers, postdocs, or students. - Broad knowledge across multiple material classes and their relevant properties (e.g., electronic, magnetic, optical, mechanical). - Deep, recognised expertise in first-principles simulation methods for materials (e.g., DFT, DFPT, MD) and a strong understanding of their application and limitations. - Extensive hands-on experience using computational packages like VASP, Quantum ESPRESSO, LAMMPS, or similar. - Strong programming skills (e.g., Python) for workflow management, data analysis, and tool automation. - Demonstrated ability to independently lead and manage complex computational research projects, from conception to data analysis and communication. - Excellent teamwork and communication skills, with proven experience in interdisciplinary collaboration, especially bridging the gap between computational/theory and experimental groups. In addition, the following would be an advantage: - Experience in developing or applying machine learning models for materials property prediction (e.g., GNNs, ML-derived interatomic potentials). - Expertise in high-throughput computational workflows and managing large-scale simulation campaigns on HPC or cloud infrastructure. - A significant track record of high-impact research, reflected in publications, patents, or deployed technologies. - Experience in strategic planning for a research group, including hiring and resource allocation. ## Skills ### Required - Computational Materials Science - Solid-State Chemistry - Condensed Matter Physics - First-principles simulation methods - VASP - Quantum ESPRESSO - LAMMPS - Python - Workflow management - Data analysis - Tool automation ### Nice to have - Machine learning models for materials property prediction - High-throughput computational workflows - HPC or cloud infrastructure - Strategic planning for a research group --- Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/deepmind/jobs/7353237?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)