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Field
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array of topics in the focus areas of energy, infrastructure, environment, materials, and chemistry and process engineering. The advertised position is part of the newly founded division 4.2 ‘Material
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data mining. The group provides a strong network to local AI expertise (e. g. Hessian.AI, TU Darmstadt), large scale compute infrastructure, as well as a broad international network (Stanford, UC San
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for multimodal inferences, combining computer-vision, environmental parameter measures and DNA data. Your role will be central in data acquisition and foremost machine-learning models creation. You will
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environment (e.g. cleanroom, laboratory Deep knowledge of solid state physics and/or quantum information Experience with microfabrication and/or operating and calibrating quantum systems Experience with
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in chemistry, physics, materials science, chemical engineering or a related subject Desirable: • Experience in one (or more) of the following areas is beneficial: metal-organic frameworks; adsorption
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
are already working towards an early start of deep-sea mining, there is still an urgent need for research on the associated environmental impacts. In the JPI-Oceans project MiningImpact, the Deep-Sea
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for data-efficient exploration and optimization within the process parameter space as well as for adaptive, data-driven machine learning to map the electrolysis process to a digital twin. Data workflows and
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, signal processing, and data mining A strong background in programming, statistical analysis, and spatial modelling and mapping Highly motivated to work on the subject and eager to work in an
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computer science with very good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience
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TUM's privacy policy. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. Data