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machine learning to objectively detect changes associated with disease progression, thus identifying features that reliably predict malignant change. Objectives: Evaluate histo-morphological features
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in human-AI interaction to join a research team focussed on studying learning and decision-making in humans and machine learning systems. The Human Information Processing (HIP) Lab is headed by Prof
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to develop a novel distributed digital twin framework. They will have skills in distributed artificial intelligence (AI), machine learning (ML), and digital twin, and strong knowledge in computer networking
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undertaking field, and laboratory postharvest storage trials. You will have proven experience in analytical technologies (i.e. HPLC, LC/MS) and data analysis (Genstat, R, or other machine learning tools) and
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analysis (Genstat, R, or other machine learning tools) and interpretation. Spanish language skills are desirable but not essential. Additional Requirements are willingness and ability to travel, as the role
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practices are desired. Good analytical skills and computer skills. An ability to work independently to a tight schedule. Capability of working effectively within a team to achieve results. Evidence of
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experience is desirable. Good report writing and presentation skills Previous laboratory experience and practices are desired. Good analytical skills and computer skills. An ability to work independently to a
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skills. An ability to work independently to a tight schedule. Capability of working effectively within a team to achieve results. Evidence of excellent organisational and communication skills. High levels
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: Earth Sciences, Bioscience, Future Propulsion and Power, Synthesis for Biology and Medicine, Modern Statistics and Statistical Machine Learning, Mathematics of Random Systems, Medical Sciences