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international conferences Supervise student theses Your Profile: Excellent Master`s degree with a strong academic background in computational engineering, mathematics, computer science, physics, engineering or a
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Tropical Silviculture and Forest Ecology Ecosystem Modelling Wildlife Management Biodiversity, Macroecology and Biogeography Landscape Resilience Course organisation The PhD programme in Forest Sciences and
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, computer science or mathematics (or a related field), with a focus on computer vision, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills Very good
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characterization and synthesis of solid-state materials is a plus • Experience in mechanochemistry is a plus • Knowledge of (or interest in) computational chemistry is a plus • German language skills are desirable
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well as the Faculties of Sciences and Engineering to develop an internationally visible research program at the intersection of their research interests and the FAU key research priority of “New materials and processes
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19 Dec 2025 Job Information Organisation/Company UNIVERSITY OF TECHNOLOGY NUREMBERG Research Field Computer science Researcher Profile Established Researcher (R3) Country Germany Application
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, earth sciences, energy systems, or material sciences University degree (M.Sc. or equivalent) in applied mathematics or in computational engineering science, computer science, simulation science with a
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, Information and Technology, Department of Computer Science. Responsibilities The responsibilities include research and teaching as well as the promotion of early-career scientists. We seek to appoint an expert
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Max Planck Institute for Biology Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 4 days ago
organisms. Our program transcends traditional life science disciplines, combining pioneering methodologies and scientific approaches from various fields to address research questions that require
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hold a Ph.D. in computer science, machine learning, bioinformatics, or related fields. The applicant should have a strong interest and prior experience in developing machine learning methods and/or