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) or other expertise relevant to the project objectives (see above) Early career track record including publications or other outputs in the related field In case your background is in psychology or medicine
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: developing and testing new approaches to water resources modelling, application of Bayesian inference methods to environmental problems, machine learning and data science applications, undertaking analysis and
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(e.g. Python, R) Experience in the use of neuroimaging analysis (fMRI, MRI) to study mechanisms of brain function Previous experience of using Bayesian methods in both model development and fitting
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-traditional, e.g., event data) and network structures (for sensor networks). In this project, we will investigate Bayesian deep learning approaches to training models under uncertainty for several sensing
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of using Bayesian methods in both model development and fitting. Previous experience and knowledge of research methods and study design in clinical trials. Knowledge of Good Clinical Practice (GCP) in
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assessment models, and statistical modeling in both frequentist and Bayesian frameworks • A solid track record of publications Appointment Type Restricted Salary Information Commensuate with experience Review
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investigator and will participate in theoretical and numerical modelling work, as part of a project team that includes doctoral students and technical staff. The main objective of this postdoc position is (1
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experiments, data analysis, field work, and work as part of a project team that includes doctoral students and technical staff. The main objective of this postdoc position is (1) to measure the activity and
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responsibility, particularly in relation to planning, funding, collaborating and publishing research, and mentoring colleagues. 15 Establish and sustain a track record of independent and joint published research
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project team that includes doctoral students and technical staff. The main objective of this postdoc position is (1) to develop theoretical modelling approaches (bioenergetics, thermodynamics, ecological