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research questions a strong collaborative spirit and enjoyment working closely within a diverse research team intellectual curiosity, creativity, and an openness to exploring new methods and
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within a joint research programme. What will be your tasks? The position focuses on the co-design and co-development of a monitoring assessment and policy framework for mitigating changes in marine
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behavioral data) using current and innovative methods Presentation of research results (in scientific journals, colloquia and conferences, manuscript publication) Requirements and Skills Excellent master and
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master's or diploma degree in computer science or mathematics already successfully completed doctorate confident demeanor and proficient use of German and English (both equivalent to at least B2) expertise
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/ research stays, and/or presentations at international conferences; Proven experience in quantitative and/or qualitative social-science methods; Willingness and ability to further PRIF’s research agenda
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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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The Leibniz Institute for Solid State and Materials Research Dresden e. V. (IFW Dresden) conducts modern materials research on a scientific basis for the development of new and sustainable materials and technologies. The institute employs an average of 500 people from over 40 nations and, in...
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people of different talents, experiences, and skills work together to learn from each other and generate new knowledge and methods to create a better quality of life. TRIGGERINK PROJECT The TriggerINK
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and skills: You hold a PhD in Bioinformatics, Computational Biology, Genomics or a related field. You bring proven expertise in deep learning and statistical modelling of biological data. You have
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) for the Information Service Engineering department (ISE) in Karlsruhe startingOctober 1, 2025. The ISE department, led by Prof. Dr. Harald Sack, investigates models and methods for efficient semantic indexing