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have recently developed a new method of statistical analysis for the problem of finding the key genes for disease, with exciting pilot results and promising drug targets for rheumatoid arthritis and
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expertise in machine learning and/or Bayesian models is preferred. This position will involve both methodology development and analysis of multi-omic sequencing data, including spatial transcriptomic data
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presentations, response to therapy, disease progression and complication, and that further subclassification of diabetes into more homogeneous groups offers opportunities for tailored and targeted early treatment
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methodologies. Understanding of integrating Bayesian approaches in NN-based model Knowledge of model deployments to cloud platforms or past work with AutoML tools. Knowledge of MLFlow for maintaining model
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Review, update, and consolidate methodologies, including Bayesian methodologies, in the context of material balance evaluation Your Profile: PhD in applied mathematics, computer science, physics, or in
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the complex development phases of new production processes faster, more cost-effective and efficient through the targeted use of AI methods. What you will do Your research will be mainly related with two sub
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possible thereafter. The aim of this project is to advance the development of multi-trait Bayesian linear regression models that enable the sharing of genomic information across traits and biological layers
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candidate, you will: Develop and apply Bayesian Network machine learning methods to analyze the dynamics of G-protein coupled receptors to uncover allosteric regulation that enables design of allosteric
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, mobility patterns, and reporting delays. The project can include development of software to implement methods, as well as further development of methodology, primarily in a Bayesian framework. There is also
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to identify and promote the voluntary adoption of effective bycatch reduction strategies in targeted fisheries. There will also be opportunities to contribute to writing research proposals and mentoring