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Field
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. This will largely advance our still limited knowledge on the intricate mechanisms of CHC perception in particular and on speciation mechanisms mediated by chemosensory evolution in general. The successful
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Max Planck Institute of Animal Behavior, Radolfzell / Constance | Radolfzell am Bodensee, Baden W rttemberg | Germany | 2 days ago
their specific research focus (for example, communication, social learning, cumulative cultural evolution, or other related themes). Your qualifications This call is open to candidates who have completed a
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%) on “Understanding the dual role of SOBIR1 and PBL30 in steering plant immunity and development”. The position is available from January 2027 and is initially funded for three years, with the possibility of extension
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31.08.2026 Application deadline : 09.10.2026 The Cluster of Excellence GreenRobust invites applications for a PhD position (m/w/d, E13 TV-L, 65%) in the field of plant immune receptor evolution in
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degree in Computer Science, Artificial Intelligence, Software Engineering, Robotics, or a related field Strong experience in software development and excellent programming skills, preferably in Python
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combining interdisciplinary scientific training, research exchange, and career development Access to state-of-the-art research environments across participating institutions Funding for annual participation
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Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 9 days ago
(full-time, with 39 hours). Job description the synthesis and characterization of organometallic complexes the development of catalytic applications and quantum chemical calculations on electronic
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Developing innovative technology solutions and bringing them to application - that is our goal at the Fraunhofer Institute for Photonic Microsystems IPMS . With our expertise in the development
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Everyone is talking about artificial intelligence. But who is developing the necessary chips? We are, for example! Would you like to help drive the development of a new highly efficient AI hardware
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of heterogeneous operational data. However, limited availability, privacy constraints, and the variable quality of real-world datasets continue to hinder the development of reliable AI solutions for energy system