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Field
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training, applied learning opportunities, and executive education for practitioners and policymakers. Housed in the Office of the Provost, CHRIS provides central leadership, infrastructure, and
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research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to innovative melanoma and skin cancer research
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, Educational Technology, Learning Sciences, Human-Computer Interaction, or a related discipline. Strong interest in research relating to Generative AI, AI literacy, digital learning, workplace learning, or human
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relevant PhD (or equivalent qualification/experience) awarded prior to commencing the appointment Ability to develop a coherent world-leading research programme Ability to plan and build a team and deliver
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to their work. About You We encourage applications from individuals with a wide range of backgrounds and experiences. You should demonstrate: Essential Criteria: A relevant PhD (or equivalent qualification
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; cost, carbon or sustainability optimisation; uncertainty and sensitivity analysis; and machine learning or AI-supported optimisation. Strong analytical and programming skills are essential. Relevant
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areas of statistics, data science, and artificial intelligence (AI). The position will focus on developing and applying novel statistical, machine-learning, and AI methods to advance biomedical and
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Materials Design - Develop and apply machine learning and AI models (e.g., ML interatomic potentials, generative design, reinforcement learning) to predict and design materials. - Perform first-principles and
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completed a PhD in engineering or computer science, or an equivalent foreign doctoral degree recognised as comparable to a Norwegian PhD. Competence in developing and applying machine learning methods Good
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system PhD in Chemistry/Materials Science/Physics Encourage initiating activities on MOF development, devising, and analytical process Experience in machine learning will be preferred Good oral and written