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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Biology-informed Robust AI Methods for Inferring Complex Gene Regulatory
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methods, including modern machine learning methods, to draw inferences from register data. A third project “Integrative machine and deep learning models for predictive analysis in complex disease areas“ is
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(causal inference and pathobiology). iii) Integrating knowledge of clinical implementation channels. Other tasks may also be assigned. Eligibility Students with basic eligibility for third-cycle studies
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) predict molecular expressions, (ii) translate computational insight into patient-behaviour, and (iii) implement both supervised and unsupervised methods to infer stroke risk from pre-operative input data
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and advanced causal inference methods to large-scale multi-omics datasets, national health registers, and other comprehensive health-related data sources. Duties The doctoral position is intended
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prehistoric individuals, to make inferences about demographic history, migration and admixture patterns, and signals of adaptation. The project will include computational analysis of archaic introgression and
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the driver to actively participate and accept the interventions. A key component in the project will be to practically test feasibility and assess the performance of algorithms and hypotheses in test track
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modern digital infrastructure from emerging network threats. Despite being young, Secura Lab has an excellent track record in publishing at top-tier security and blockchain conferences. At Secura Lab, we
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generative models, AI/ML, polymers, and/or materials science Documented track record of research in the area of the project What you will do Design and implement deep learning (DL) workflows for learning from
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: Knowledge in deep generative models, AI/ML, microscopy, and/or molecular design Documented track record of research in the area of the project What you will do Design and implement deep learning (DL