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analysis of complex, longitudinal, and high-dimensional data (e.g., immunometabolic profiles, clinical data, biomarkers). Development and application of predictive models and algorithms for diagnostics
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setting. In this environment, our research group focuses on combining novel genome engineering tools (e.g., CRISPR-based) and computational algorithms to enable regenerative cell therapies. Now, we are
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of >10 members, including a full-time senior PhD statistician and both clinical and full-time postdocs. Our projects typically leverage large sets of either registry-based, biomarker, genetic and/or
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, teachers, technical/administrative staff, and Ph.D. candidates. The department has a large PhD programme and co-ordinates three international Master programmes. The Department has a well-established
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working time will be devoted to your own research but you will also be expected to co-supervise graduate students and collaborate with PhD-students. In addition, you may take part in other teaching
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society Administration related to the work duties listed above Qualification requirements Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed
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and supervision of PhD students as well as collaboration with theory groups to establish theoretical understanding of the results. Qualification requirements Appointment to a post-doctoral position
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should include: a cover letter describing your scientific background and goals for this post-doctoral period (max. one A4 page), a CV including a full publication list, a copy of the PhD certificate
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group consists of four associate researchers and one PhD student. Within the group, we value a positive work environment characterized by respect and care in our interactions. We continuously strive
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite