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-end technologies (e.g., Node.js, Python/Django/Flask, REST APIs, SQL/NoSQL databases) Demonstrated knowledge of AI/ML methods, such as supervised learning, NLP, or deep learning, with application
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authentic learning experiences within real-world settings. Through strategic partnerships forged by our academic staff with industry, learners bridge theoretical knowledge with practical application inside
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/programme management experience with the ability to juggle and complete multiple projects with diverse stakeholders within an academic or healthcare setting. Working knowledge in research ethics and HBRA is
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software tools (e.g., NVivo, MAXQDA) to identify actionable insights. Translate complex data narratives into practical recommendations for stakeholders, practitioners, and policymakers. 3. Knowledge
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, corporate financial statements, and credit risk analysis, is required. A thorough knowledge of the research field of sustainable economics or finance is highly preferred. Quantitative analytical and/or
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. Basic understanding of financial sector (banks and other financial institutions), financial markets, corporate financial statements, and credit risk analysis, is preferred. A thorough knowledge of the
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. Basic understanding of financial sector (banks and other financial institutions), financial markets, corporate financial statements, and credit risk analysis, is preferred. A thorough knowledge of the
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, Neuroscience, or another relevant area Extensive knowledge of ALS Experience of iPSC differentiation and mouse models of ALS Experience of phenotyping iPSC-derived cells Experience of advanced molecular biology
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. Collaborate with interdisciplinary team members from partner institutes. Assist in supervising research assistants and graduate students where applicable. Contribute to knowledge dissemination through
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. Critical thinking and scientific achievement in research, exemplified by publications, conference presentations or patents. Experience: Excellent knowledge and mastery in one or more of the skillsets below