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peer-reviewed journals, the preparation of a doctoral dissertation (monograph), and active participation in the collective work of the research team, which consists of the PI, a postdoc and three PhD
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do grau. b) Experiência comprovada em investigação científica na área temática de Cultura e Políticas Culturais. c) Experiência comprovada de atividades de extensão e disseminação de conhecimento e
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://www.tudelft.nl/en/2026/tbm/tpm-researchers-receive-nwo-kic-consumer-behaviour-for-a-circular-system-transition-grant . The project includes 2 PhD positions, 2 Postdoc positions, and several researchers
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(ILM), interacting with PhD students, postdocs, and master's students on related topics. We seek a motivated candidate holding a master's in physics, with skills in ultrafast/nonlinear optics or soft
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with experience applying these models to practical applications for real-world challenges. Good programming skills, Python is mandatory, other languages (e.g., Java, C++) will be considered a plus to
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discipline. Essential Good programming skills, preferably in Python/C#. Experience with machine learning, deep learning, or experimental AI evaluation. Interest in secure distributed AI, federated learning
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evidence of excellent study results. You have strong programming skills in C and at least one high-level language (e.g. Python). You have a solid understanding of wireless network stacks and/or experience
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(e.g., Python, MATLAB, C++, etc). Strong written and verbal communication skills. Please contact the main supervisor, Dr Emily Manchester - [email protected] . Please send your CV and a
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experience in modeling (60%); b) Experience in participating in research projects (20%); c) Experience in programming in Python and related languages (20%). 10. Selection Jury Composition: Ana Isabel Pereira
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applicants only, submission via postal mail): LMU Munich Doctoral Training Programme in the Learning Sciences c/o Studiengangskoordination Leopoldstr. 13 80802 München Germany Possibility of finding part-time