The department "Metallic and Hybrid Materials" of the Institute of Materials Research works in the fields of development and optimization of modern metallic materials for aerospace applications. Computational methods like CALPHAD (CALculation of PHAse Diagrams) and ab-initio methods are used to understand the thermodynamics and structure of materials to predict their properties and understand their behaviour. The combination of these methods with multidisciplinary optimization algorithms and machine learning is applied to accelerate the analysis and development of materials. The relationships between process, structure and properties are finally investigated through advanced mechanical testing or synchrotron tomography techniques.
The Quantum Computer Initiative is a major project of the German Aerospace Center funded by the Federal Government in the field of development and use of quantum computers. The aim of "QuantiCoM - Quantum Computing for Materials Science and Engineering" is to use quantum computers for the rapid development of materials in order to find sustainable solutions for a circular economy.
Your tasks:
You are part of a team that develops, implements and uses experimental and computational tools to determine the properties of engineering materials.
You will develop hybrid algorithms for quantum computers and apply them on real machines.
You will investigate the power of quantum machine learning and optimization.
Based on your results, you will develop further numerical and physical experiments.
You will supervise PhD students and manage work packages.
Become part of our team and lay the foundation for the future development of quantumbtechnologies and materials science.
The position also allows participation in the DLR educational programme.
How to apply
You can submit your application via the DLR job portal
Quantum Computing for Materials Science and Engineering - PostDoc
The department "Metallic and Hybrid Materials" of the Institute of Materials Research works in the fields of development and optimization of modern metallic materials for aerospace applications. Computational methods like CALPHAD (CALculation of PHAse Diagrams) and ab-initio methods are used to understand the thermodynamics and structure of materials to predict their properties and understand their behaviour. The combination of these methods with multidisciplinary optimization algorithms and machine learning is applied to accelerate the analysis and development of materials. The relationships between process, structure and properties are finally investigated through advanced mechanical testing or synchrotron tomography techniques.
The Quantum Computer Initiative is a major project of the German Aerospace Center funded by the Federal Government in the field of development and use of quantum computers. The aim of "QuantiCoM - Quantum Computing for Materials Science and Engineering" is to use quantum computers for the rapid development of materials in order to find sustainable solutions for a circular economy.
Your tasks:
You are part of a team that develops, implements and uses experimental and computational tools to determine the properties of engineering materials.
You will develop hybrid algorithms for quantum computers and apply them on real machines.
You will investigate the power of quantum machine learning and optimization.
Based on your results, you will develop further numerical and physical experiments.
You will supervise PhD students and manage work packages.
Become part of our team and lay the foundation for the future development of quantumbtechnologies and materials science.
The position also allows participation in the DLR educational programme.
