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Ideally, initial experience in a technical or scientific environment (e.g. cleanroom, laboratory) Knowledge of solid state physics and/or quantum information Experience with programming, preferably with
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, with an interest in probability theory, mathematics, and data science. Very good practical C++ and Python programming skills allow you to make your ideas happen. Very good command of written and
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following: Scanning probe microscopy, transport measurements, superconductivity Programming experience, for scripting and data analysis Very good command of written and spoken English with extensive
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background in numerical methods, mathematical modeling, and network simulation or analysis Good understanding of power systems, gas networks, or coupled multi-energy systems Proficient in programming
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numerical modelling and scientific programming in MATLAB Basic understanding of battery systems, electric vehicles, energy systems or power grids Experience with model predictive control, multi-objective
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modelling Experience in scientific programming and numerical simulation using MATLAB and/or Python, as well as in processing and analysing experimental data Practical experience with laboratory battery
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strongly desired Programming experience in Python and familiarity with machine learning frameworks Knowledge of emerging memory devices and computing technologies is beneficial Excellent communication
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programming neural networks, machine learning theory and machine learning software frameworks (e.g., PyTorch or JAX). Curiosity-driven personality with the ability for creative and analytical thinking
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analyzing scientific literature and patents Strong interest in energy technologies and energy systems research Experience in LLMs and developing LLM-based methods is an advantage Programming skills
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programming and applied mathematics, and interested in neural networks and their hardware implementation. Some experience in machine learning would be an asset. Prior knowledge of emerging memory