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Field
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preferred skill, including GIS, spatial suitability modeling, multi-criteria decision methods, and machine-learning-based feature importance. Exposure to resource questions relevant to large-load development
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focused on precision lung cancer prevention and early detection, with an emphasis on risk prediction modelling using artificial intelligence and machine learning. Major duties and responsibilities include
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information-security approvals required by the programme, and engage with internal University stakeholders (IT, HR, Teaching & Learning, faculties) and external partners. We welcome candidates who bring diverse
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, and laboratory operations. Job Requirements: PhD in Electrical Engineering, Computer Engineering, Physics, or a closely related discipline. At least three years of relevant research experience in
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reactions. Experience applying Machine Learning to optimise and guide iterative laboratory experiments. Experience of oligonucleotide design and of adapting an amplification method to new target sequences
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projects and deliverables May supervise undergraduate students working on the AI/ML projects QUALIFICATIONS PhD (or equivalent) in Machine Learning, Computer Science/Engineering, Biomedical Engineering, or
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acquired across multiple anatomical regions to form a patient-level assessment. This PhD project will investigate novel deep learning methodologies that jointly model anatomical structure and prediction
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assigned by Supervisor. Requirements PhD in Computer Science or related field Expertise in computer vision and vision-language models Experience with ML evaluation metrics and benchmarking Proficiency in
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dataset analysis, machine learning tools, and relevant computational biology approaches • Document, compile, and format data analysis in presentations and reports to supervisor. • Mentors and trains
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Engineering, who have received recently a PhD degree or passed a viva. Expertise in finite element analysis (especially ANSYS), the skills allowing to create Python-ANSYS interfaces and using machine-learning