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for doctoral education . Skills and personal qualities Necessary: Experience with developing, evaluating and explaining state-of-the-art machine-learning algorithms, with a strong focus on deep learning
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functions. Other responsibilities include development of methodology and work routines, literature review, statistical analysis, adhering to the lab policies, assisting with administrative tasks and drafting
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missing data, multiple imputation (MI), has not been assessed in the settings of cancer epidemiology. This project aims to fill this gap in the literature, leading to significant methodological advancements
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responses to acute infections and cancer. Using a combination of several state-of-the-art single-cell technologies we strive to understand mechanisms underlying the generation, maintenance and consequences
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state-of-the-art molecular biology techniques with advanced imaging to ask how mechanical cues and cell-cell junctions govern heart regeneration in salamanders. Moreover, the group utilizes cardiac
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an international environment. Desirable: Programming skills in R and Python is considered a strong merit. Familiarity with literature search and reviewing and summarizing scientific articles. Knowledge of research
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therapies for children with cancer. We do this by applying several different methods and techniques, including cell barcoding to study individual tumor subclones, state-of-the-art organoid technologies, high
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of the art in situ hybridization, bioinformatic analysis and working with animal models. The student will interact with clinicians at the rheumatology clinic and international collaborators. The student is
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access to a wide range of state-of-the-art omics and high throughput methods by our close proximity to SciLifeLab facilities. In close affiliation to the research group we also provide access to MS-based
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developed a unique automated robotic lab for high-capacity full-length scRNA-seq that can provide state-of-the-art splicing information across complex tissues. Using this scalable scRNA-seq technology, we