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methodological development and application of bioinformatics, biostatistics, machine learning, and data management within clinical research. CLINDA is interdisciplinary and employs biostatisticians
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Assistant Professor in statistics for the development of privacy-enhancing techniques in health care
dedicated to bridging clinical practice and data science. It comprises three research groups: (1) Clinical AI, (2) Bioinformatics and Statistics, and (3) Data Science Methods. The PhD student will be part of
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competencies Applicants must hold an MSc degree in statistics, genetic epidemiology, bioinformatics, clinical data science, medicine, or a related field. Programming skills (e.g., R, Python, or similar) and
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, computer science, bioinformatics, computational biology or biostatistics Proven expertise in machine learning applied to molecular or other high-dimensional data Experience working with IBD or other immune-mediated
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expected to lead and coordinate interactions in an interdisciplinary team involving internal and external collaborators from multiple fields. Your Competencies • A master's degree, in Bioinformatics
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research groups: (1) Clinical AI, (2) Bioinformatics and Statistics, and (3) Data Science Methods. The PhD student will be part of the Data Science Methods group, which has a strong research focus on privacy
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) Bioinformatics and Statistics, and (3) Data Science Methods. The postdoc will be part of the Data Science Methods group, which has a strong research focus on privacy-preserving techniques. CLINDA includes 17 core
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science, bioinformatics, engineering, or a related data science discipline. Applicants must have documented research experience within artificial intelligence, machine learning, computational methods, or data-driven