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Description In the Leibniz Institute of Plant Biochemistry, the independent research group Receptor Biochemistry invites applications for a PhD position in (bio)chemistry (m/f/d) (Salary group E13
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. Research Focus The rise of powerful Large Language Models (LLMs) and autonomous AI agents is set to fundamentally change the practice of software engineering. As AI evolves from simple co-pilots to agents
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Description Who We Are: The Cutsail research group at Ludwig-Maximilians-Universität (LMU) Munich is seeking a highly motivated PhD student / research assistant for full-time, on-site work in the
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Specifications. The PhD topic consists of two parts, the weighting of which can be adjusted. First, natural frequencies of different UAV categories for different power settings shall be modelled. Second, based
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Design and implement optimization techniques for full-stack improvement of quantum algorithms Model major sources of experimental error for control theory or for error mitigation techniques Scientific
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in vitro platforms and humanized mouse models Your Profile: Required qualifications: PhD in virology, immunology, or a related field Degree in life sciences, human medicine, or veterinary medicine In
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for the German public sector. This is a position for PhD. TUM is an equal-opportunity employer. Therefore, women are especially encouraged to apply. We hope this position can start in 2025. Applications Complete
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Max Planck Institute for Nuclear Physics, Heidelberg | Heidelberg, Baden W rttemberg | Germany | 17 days ago
strong links to theory groups at the institute and astrophysical interpretation and modelling work may also be included. PhD in Physics or Electronic Engineering. Knowledge of relevant technologies and/or
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a high quality of life in Dresden, with its dynamic urban scene, relatively affordable living, rich cultural offerings, and vibrant nightlife. Further questions regarding the open PhD positions can be
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=25541 PhD position - Functional and molecular characterization of AI-based morphological predictors