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models that are more efficient, inherently multimodal, and capable of processing information at an unprecedented scale. Key research questions include (but not limited to): Non-Autoregressive and Diffusion
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-reads) for microbial ecology studies and finally, you have capacity for handling large amounts of data and their suitable storage and dissemination according to FAIR principles. Position 2: Postdoc in
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, ranging from biological to clinical features. The integration of such heterogeneous information within a coherent computational model is currently challenging, due to the typical large dimension and
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in new methodology development in computational protein design, leveraging the large amount of data that is generated by various groups and departments at St Jude. As an institutional center
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and epidemiological characterisation of cardiovascular risk among people living with T1D, using multimodal data in the large SFDT1 cohort study. This work will lay the groundwork for developing novel
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at the intersection of Genomics, Personalized Medicine, Epidemiology, and Artificial Intelligence (AI). A key initiative within the school is the Human Phenotype Project—a groundbreaking, large-scale longitudinal
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. They will work in highly-technical, multi-disciplinary teams and offer deep technical understanding of cloud computing technologies, DevOps practices, networking, IT and Big Data solutions and business
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training students Maintain analytical equipment Cooperate with other large collaborative projects of the research group Qualification: Required: A diploma and a PhD in microbial natural product chemistry
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of the extracts; LC-MS and bioactivity-guided isolation and structure elucidation of the purified metabolites Supervising and training students Maintain analytical equipment Cooperate with other large collaborative
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coordinates multiple large-scale research projects and globally unique data resources, such as FinnGen, nationwide health registry data and the Finnish Twin Study and leads the molecular profiling of cancer