Computational Materials Scientist

We are looking for candidates with an excellent research record and with educational competence within the fields of Computational Materials Science and Engineering or related areas to perform research on designing material structure, predicting material properties and behavior. The job will require the consideration of a broad range of applications where materials performance plays a critical role, e.g., materials stability, microstructures, and functional and mechanical behaviors of materials. This role requires experience in integrating and implementing various existing or novel modeling methods to bridge length and/or time scales (i.e., multiscale approach), enabling the simulation of complex materials under application conditions and investigate material  As such, the job role requires strong collaboration with experimentalists, and other modeling experts. Integrating physics-based and data-driven modeling capabilities with experimental data on a wide range of materials properties is another main technical task of this job.

What you will do

• You will use multiscale, multi-physics, and data-driven modeling capabilities and simulation approaches to derive structure-process-The successful candidate has experience in integrating traditional physics-based methods with data-driven methods (e.g., Machine Learning, Materials Informatics) to address these challenges allowing model-based in-silico design of materials.
• We also require subject matter expertise in materials science or related fields, e.g. polymers including polyolefins, soft matter, composites, etc. You will need to be able to identify and investigate various physical processes and mechanisms at multiple length and time scales, while integrating all aspects of the discovery and development framework.
  

About You

• PhD in materials science and engineering, chemical engineering, chemistry, computational chemistry, physics, computational physics, or a related degree
• At least 3 years of materials modeling research experience (including PhD research)
• Expertise in multiscale and multi-physics materials modeling and calculations of material properties and performance using a broad range of techniques from ab initio to molecular mechanics, and statistical informatics approaches, and proficient with atomistic simulations, density-functional theory, molecular dynamics, coarse grained methods, and/or continuum methods (e.g. finite element analysis/methods) as well as corresponding modeling software packages
• Extensive coding experience, preferably with fluency in Python or other scripting languages for automation and C++
• Experience with high performance computing and massively parallel computer systems
• Ability to propose, implement, and lead new approaches to accelerate materials discovery and development
• Excellent communication with strong ability to develop partnerships and relationships across functional areas, and strong collaboration skills with experimentalists (e.g., chemists, analytical scientists, engineers)
• Experience with developing and deploying computational tools for materials research, and ability to convince users to utilize new tools and facilitate their implementation.

• Polymer science/physics, soft matter physics, fluid mechanics
• Research experience with material development addressing emerging energy and sustainability needs
• Thermodynamics, statistical mechanics, and kinetic modeling