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Field
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be advantageous: Experience with scientific expeditions Experience in computer-aided analysis of biological sequence datasets (e.g., with R, Python and Bash/Linux environments) Basic understanding
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(meta-)genomes Experience in the computer-assisted analysis of large biological datasets (e.g., using R, Python, and Bash/Linux environments) Very good written and spoken English skills Ability to work
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and is associated with the management of the Institute's own 500 m² clean room facilities (https://www.igm.uni-stuttgart.de/en/research/clean_room_lab/ ). We are looking for an individual with
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thus expected to possess the necessary English language skills. Also expected is the willingness to eventually offer courses in German after the tenure evaluation. Where to apply Website https
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and uncover yet unknown physiological particularities of sleep and other human health factors. Your Profile PhD (or near completion) in Biomedical Engineering, Computer Engineering, Computer
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
to decode the complexity of tissues and shed light into cancer biology. Our interdisciplinary team — comprising biologists, engineers, computer scientists, and medical researchers — develops next-generation
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Leibniz Centre for Agricultural Landscape Research (ZALF) | Gie en, Hessen | Germany | about 1 month ago
. The resilient value networks should integrate horizontal linkages between different actors of the farming system (producer, processor, retailer, consumer) and thereby expands the value chain concept of a vertical
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of geoscientists, biologists, and computer scientists at the Universities of Tübingen and Hohenheim and the Senckenberg Institution of Biodiversity and Earth System Research in Frankfurt, investigating how
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, computer-based imaging and morphometric skills for the study of material culture, skills in technological and/or functional analysis, organic artifacts, or experimental archaeology approaches. The Department
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architectures for foundation models The work will combine methodological development with large-scale experiments, aiming for contributions at leading machine learning and computer vision venues such as NeurIPS