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Field
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AI/machine learning, and data analysis using MATLAB or Python. Provide technical assistance on related research projects, such as preparing progress presentations and reports for funding agencies
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of an undergraduate degree in a related field. Training in causal inference and/or machine learning methods Effective oral and written communication skills Outstanding academic credentials and intellectual creativity
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postdoctoral Research Fellow (RF) position for one year with a possible extension for one more year. The starting date is November or December 2025. This post will advance the application of Machine Learning (ML
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, glioblastomas, colon cancer, and lung cancer. Advancing precision oncology through machine-learning models: We integrate multimodal patient data, including multiomic data and health record information, to develop
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Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information clearly Informal
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). The objective of this project is to enhance malaria control programs in Peru, Ecuador, and Brazil by expanding and improving early warning and surveillance systems, and modeling the impacts of coordinated
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antigens, T cell receptor (TCR) and antigen interactions and their crucial role in anti-cancer immune responses. You'll leverage your strong background in computational biology, machine learning, and
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experiments to validate findings from the omic studies. The desired skill set is split between dry lab (bioinformatics) and wet lab (basic science/animal models). Additionally, the individual will be required
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of innovative computational procedures and methodologies, addressing a national skills shortage and enabling timely progress on a high-impact research initiative in modern econometric modelling. The role provides
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in statistics, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded