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) at the Department of Computer Science, aligning with concurrent projects developing foundation models for healthcare. The groups are active members of the ELLIS Institute Finland (https://www.ellisinstitute.fi
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and the Probabilistic Machine Learning Lab (https://www.helsinki.fi/en/researchgroups/probabilistic-machine-learning ; groups of Acerbi and Klami) at the Department of Computer Science, aligning with
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to align with the key themes of the research project, specifically those related to state, refugee and corporate infrastructures, applicants are encouraged to implement approaches to the topic relevant
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of childhood and adolescent multimorbidity, as well as the mechanisms linking these and other prenatal and perinatal exposures to subsequent multiple chronic diseases. The work will focus on analysing large sets
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Methods for Virtual Labs: Constructing interactive "virtual laboratories" where medical professionals can interact with, audit, and align LLM-powered medical agents with clinical guidelines
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several key events to an adverse outcome across multiple biological levels) Build documented, reproducible and reusable computational workflows for collaborative research Scientific contribution and
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on a broad range of topics, including advanced physical layer design, multiple-antenna systems, reconfigurable intelligent surfaces, integrated sensing and communications, non-terrestrial and UAV
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for 6G and beyond wireless technologies. We work on a broad range of topics, including advanced physical layer design, multiple-antenna systems, reconfigurable intelligent surfaces, integrated sensing and
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together leading European partners to investigate early-life determinants of immune system development through large-scale, longitudinal multi-omics studies, integrating data across multiple birth cohorts