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candidates with strong expertise in Bayesian methods, uncertainty quantification, and/or machine learning applied to nuclear theory. The group’s research spans a wide range of topics including nuclear
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/2019 , of January 25th. The presentation of such Recognition is mandatory for contract signature. More information can be obtained in: https://www.dges.gov.pt/en/pagina/degree-and-diploma-recognition
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and neural network methods will be used to transfer diagnostic capability between structures in a population. Bayesian approaches will also be emphasised. The Research Associate will take a leading role
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for boosting green and digital innovations”, Project ID 101186592, https://cordis.europa.eu/project/id/101186592 , running between February 2025 and January 2030 and funded by European Research Executive Agency
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-Track) Department: Medicine | School Biomed Sci - Biomedical Informatics Division of Biostatistics and Population Health (BPH, https://medicine.osu.edu/departments/biomedical-informatics/divisions
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confidential basis until the completion of the search process. Inquiries, nominations, referrals, and CVs with cover letters should be sent via the Isaacson, Miller website: https://www.imsearch.com/open
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· Demonstrable problem-solving skills · Ability to propose and apply novel (literature based) and innovative ideas for solving a problem Desirable · Knowledge of Bayesian uncertainty techniques
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Statistics or Mette Olufsen or Kevin Flores from Mathematics. Applicants with experience in Bayesian modeling, spatial statistics, mathematical modeling, data integration, uncertainty quantification and/or
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– a public-private partnership conducting phase II trials of new regimens for the treatment of tuberculosis (https://www.unite4tb.org/). Application of Bayesian methods for evidence synthesis
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Statistical Analysis Plan guidance (APT-SAP)’ project (https://sheffield.ac.uk/ctru/current-trials/apt-sap ). Provide high-quality statistical advice and support to multidisciplinary research projects within