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profile PhD in Mathematics, Theoretical Computer Science, Information Theory, Physics or related fields High level of mathematical maturity Experience with topics related to quantum LDPC codes and decoding
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As a Data Engineer, you will play a central role in the development and operation of the University’s modern data platform. You will design, build, and maintain scalable data pipelines that support
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implement an integrated, data-driven digital twin of the national energy system, capable of simulating and analyzing multi-energy infrastructures (electricity, heat, gas, hydrogen) across spatial and temporal
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experimental and numerical approaches. Materials classes of interest include components (monomers, polymers, additives, (nano)particles, etc.) utilized in high-performance polymeric materials with relevance in
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implement an integrated, data-driven digital twin of the national energy system, capable of simulating and analyzing multi-energy infrastructures (electricity, heat, gas, hydrogen) across spatial and temporal
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properties are attributed to light capture for photosynthesis and radiative heat dissipation for temperature management, whereas the role of structural leaf surface properties, such as the presence of bumps
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electrical engineering, automation, computer engineering, or a closely related discipline, with proven expertise in the operation and control of intelligent energy systems. Experience and skills Solid
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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computational methods, that leverage high-performance computing power, to develop advanced tools. The successful candidate will be expected to develop machine learning methods that integrate physical
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Software (HANDS) research unit, focuses on assessing and enabling trustworthy AI adoption through methods and tools for compliance, readiness, and performance evaluation. How will you contribute? We