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Field
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colour centre spins. Your work supporting and further develops the fabrication of these chips, i.e. together with 1-2 PhD students, you will work on the sample process line involving several cleaning steps
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profile A Master's Degree, Diploma, State Exam, or equivalent qualification in law Prior knowledge in IP law gained through a specialization or relevant study curriculum Fluency in English; a good knowledge
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research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong communication skills in English and good knowledge of French
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field. Strong background in machine learning, particularly deep learning and natural language processing. Experience with transformer-based architectures (e.g., BERT, GPT) is highly desirable. Proficiency
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areas is considered a merit: - Multi-modal data processing for decision-making in natural environments - Terrain classification and multi-layered environment mapping - Digital twin generation for natural
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SD-25157 RESEARCHER IN ATMOSPHERIC PLASMA TREATMENT OF METALLIC SURFACES FOR INDUSTRIAL APPLICATIONS
combination of plasma diagnostics (e.g. OES) and surface characterization techniques (FTIR, SIMS, XPS), the project seeks to develop a scientifically grounded, scalable plasma treatment process. The outcome
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journals - Enthusiasm for collaborative, interdisciplinary research - Strong written and verbal communication skills in English Why Join Us? - World-class research environment: Work at South Korea's
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Worldwide R&D Projects. Previous experience in one or preferably more topics from these areas is considered a merit: - Multi-modal data processing for decision-making in natural environments - Terrain
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and men. Project overview The project concerns applying supervisory control theory to security in a broad sense, both as off-line and on-line approaches. The work is collaborative in nature, bridging
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highly interdisciplinary project Interest in the topics of one of the two projects Bonus: Experience working with social media data, mental health, social networks, natural language processing, experiment