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data interoperability across platforms. Your Profile: Masters and PhD in Mechanical Engineering, Chemical Engineering, Computer Science, or a closely related field with a focus on renewable energy
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include: Researching, in particular, publicly available data on current and future materials for energy technologies Implementing the materials in our technology database and in our energy system model
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substitution options within the energy system Implementing the phased-out material flows and their substitution options in our technology database and in our energy system model ETHOS.FINE Deriving demand
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, physics, computer science, mathematics, electrical/electronic engineering or a related subject Strong programming skills (Python) Familiarity with machine learning and deep learning frameworks (e.g
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, or algorithms to integrate neuromorphic-inspired computing paradigms. Your main tasks will include: Identify areas where neuromorphic-inspired paradigms can be applied Develop concepts to integrate CMOS circuits
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, thermodynamics and practical laboratory work Experience with hydrogen technologies, dehydrogenation reactions, catalysis and partial reforming is advantageous Computational competencies for data analysis and
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, computer science, mathematics or other related subject (you do not need a background in Quantum Computation/Optimization) Good programming skills Useful expertise for the project: Graph Theory/Network
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Engineering or Chemistry, Physics or Informatics Experience with experimental work and characterization techniques Demonstrated experience in programming, particularly in Python, with a robust understanding of
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for licensing, spin-offs or cooperations for business and society. Your tasks in this exciting job in detail: You develop data- and technology-driven business models, carry out market and technology assessments
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, Energy Systems, or a related field of study Interest in Energy systems analysis, integration of renewable energy sources, grid resilience Good Knowledge in electrical networks analysis and simulations Good