Master’s Thesis Worker, Quantum Algorithms for Materials Science

Are you all about science and technology? Would you like to work in a meaningful role with real responsibility and excellent learning opportunities? Do you want to work with superb colleagues who are experts in their field to drive a sustainable future and tackle the greatest challenges of our time? VTT might be just the place for you. VTT is one of the leading applied research organisations in Europe. What unites us are curiosity, a passion for learning, and a purpose: to solve the biggest challenges of our time and turn them into sustainable growth and well-being. Our cross-disciplinary community of over 2000 brilliant minds from 55+ different nationalities focuses on creating impact through science-based innovation. Get to know us further by exploring VTT's tech & infra . We are now looking for Master’s Thesis Worker to join our ProperTune AI team. Join us - and let’s make an impact together! As a thesis worker, you will investigate how the first generations of logical qubits can be utilised in quantum-computing applications relevant to materials science. You will implement and benchmark materials-science quantum algorithms on logical-qubit architectures, emphasising the transition from noisy intermediate-scale quantum (NISQ) to logical intermediate-scale quantum (LISQ) computing, and compare the performance and accuracy of algorithms executed with physical and logical qubits. The project aims to develop quantum algorithms that can be validated on VTT's current and future generations of quantum computing platforms. Read more about VTT’s quantum-computing platforms: https://www.vttresearch.com/en/news-and-ideas/iqm-quantum-computers-supply-finland-world-leading-superconducting-300-qubit-quantum You will work to develop VTT ProperTune®, which is a unique, Integrated Computational Materials Engineering (ICME) based methodology to solve complex material problems and to invent totally new materials with unprecedented properties. VTT ProperTune® combined with tailored experimental capabilities and powered by data and AI methodology, form together Materials Acceleration Platform (MAP) concept utilized at VTT. Combining high-quality data with advanced data analytics and the use of AI is the booster for research productivity and new research services for VTT’s customers. In addition to applying AI methods for materials research, we work on High Performance Computing utilizing fastest supercomputer in Europe, the LUMI, and VTT’s own quantum computers. Our objective is to accelerate new material development with data driven and computationally fast solutions and that way to support the development of new materials needed in green transition and enabling development of new material applications. Read more about our VTT ProperTune® concept: https://www.vttresearch.com/en/ourservices/computational-material-design-vtt-propertune As Master’s Thesis Worker, you will: Apply advanced mathematics, quantum mechanics, computational physics, and machine learning methods to develop and analyze quantum algorithms, error-mitigation techniques, and error-correction strategies for materials-science applications. Investigate the transition from noisy intermediate-scale quantum (NISQ) computing to logical intermediate-scale quantum (LISQ) computing. Evaluate the impact of qubit and gate noise models, error suppression, and error-correction strategies on algorithmic performance. Perform numerical simulations and data analysis using high-performance computing resources. Collaborate with quantum-computing researchers and participate in discussions on future quantum-computing architectures and applications. Contribute to the long-term goal of validating quantum algorithms on VTT's quantum-computing hardware. Who we are looking for: You are a Master's student in physics, quantum technology, mathematics, computer science, materials science, or a related field. You have a strong background in mathematics, including linear algebra, probability theory, numerical methods, or related advanced topics. You have a relevant background in quantum mechanics and a genuine interest in quantum computing. You have experience in scientific programming and numerical simulations (e.g. Python, Mathematica, MATLAB, Julia, C/C++, or similar). Experience in quantum computing, machine learning, high-performance computing, quantum error correction, or materials-science simulations is considered an advantage but is not required. As a person, we hope that you are: A curious and analytical thinker who enjoys applying mathematics and physics to solve challenging scientific and technical problems that may require studying complex concepts in depth. Comfortable working independently on open-ended research questions where solutions are not known in advance. Persistent in your efforts to understand difficult topics and capable of working through long and technically demanding scientific literature. Excited by the mathematical and engineering aspects of quantum comput