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found using the classical algorithms (from 1) with Quantum Optimization Ansatz (from 3) Your Profile: Enrolled as master student in a university Good background in physics, electrical engineering
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information from experiment data Evaluation and development of specialized and/or interpretable machine learning approaches for the domain of materials science, physics, microscopy Incorporation of machine
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simulations of CG model enzymes and their constructs to optimize the overall catalytic activity. The work will be done in collaboration with Prof. S. Kondrat from the Institute of Physical Chemistry in Warsaw
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. Work with large language models (LLM) and deep learning algorithms to drive the inverse design of materials and uncover new physical and chemical phenomena. Ensure the integration and effectiveness of AI
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H2 profiles in collaboration with our modeling department Your Profile: MSc in meteorology, physics, chemistry, environmental sciences or a related field with good final grade (German system equivalent
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"Electrochemical Process and System Technology" with a total of around 30 employees at IEK-9. Your tasks in this exciting and dynamic environment: Strategic further development of the newly formed department by
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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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interpretable machine learning approaches for the domain of materials science, physics, microscopy Incorporation of machine learning results with simulation methods Working on project-related tasks where you can
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: Very good performance in your Master`s degree in the fields of energy technology, mechanical engineering, materials science, civil engineering, industrial engineering, physics, resource management
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of soft- and hardware infrastructure Close collaboration with automation experts, data and material scientists to improve and use a fast and reliable electrochemical testing process Your Profile: Master