Quantum Algorithms Researcher, Materials Science MSc Thesis

Moventas Wind Ltd; Espoo; On-site; EUR 13,000 - 20,000; Full time

Job summary

VTT in Espoo seeks a Master’s Thesis Worker for quantum-algorithms research in materials science. You will implement and benchmark algorithms on logical-qubit platforms, comparing physical vs. logical qubits, and contribute to the MAP-based Materials Acceleration Platform.

Join a team using AI, HPC, and quantum computing to accelerate new materials for green transition, with access to LUMI supercomputer and future quantum hardware.

Qualifications

• Master's student in physics, quantum technology, mathematics, computer science, materials science.
• Strong background in mathematics, including linear algebra, probability theory, numerical methods.
• Background in quantum mechanics and genuine interest in quantum computing.
• Experience in scientific programming and numerical simulations (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 advantageous.

Responsibilities

• Apply advanced mathematics, quantum mechanics, computational physics, and ML methods to develop quantum algorithms and error-correction strategies.
• Investigate transition from NISQ to LISQ computing.
• Evaluate effect of noise models and error-correction on algorithmic performance.
• Perform numerical simulations and data analysis using HPC resources.
• Collaborate with quantum-computing researchers and discuss future architectures.
• Contribute to validating quantum algorithms on VTT's quantum hardware.

Skills

Python

MATLAB

Mathematica

Julia

C/C++

Numerical simulations

Machine learning

Education

Master's student in physics

Master's student in quantum technology

Master's student in mathematics

Master's student in computer science

Master's student in materials science

Tools

Qiskit

HPC

Python

MATLAB

Job description

VTT in Espoo seeks a Master’s Thesis Worker for quantum-algorithms research in materials science. You will implement and benchmark algorithms on logical-qubit platforms, comparing physical vs. logical qubits, and contribute to the MAP-based Materials Acceleration Platform.

Join a team using AI, HPC, and quantum computing to accelerate new materials for green transition, with access to LUMI supercomputer and future quantum hardware.