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areas such as machine learning, optimization, scientific software development and high-performance computing. The division is an important part of the eSSENCE e-science collaboration and of the Science
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theory in a variety of subfields of statistics relevant to AI-enabled experimentation, including: experimental design, clinical trial design, and sequential experimentation Bayesian optimization and
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sequential experimentation Bayesian optimization and active learning contextual bandits, reinforcement learning and online experimentation causal inference and treatment-effect heterogeneity statistical
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sequential experimentation Bayesian optimization and active learning contextual bandits, reinforcement learning and online experimentation causal inference and treatment-effect heterogeneity
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trial design, and sequential experimentation Bayesian optimization and active learning contextual bandits, reinforcement learning and online experimentation causal inference and treatment-effect
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activities in areas such as numerical analysis, mathematical modelling, development and analysis of algorithms, machine learning, optimization, scientific software development and high-performance computing
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the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic
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interactive user-facing systems. The role includes support for integration, development, deployment, maintenance, UI/UX, containerization, automation, and system-level optimization. Please contact Jess
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; while they are trained using GPU-based optimization methods, the actual information processing takes place without a GPU, making them energy-efficient and fast. Diffractive networks are to be designed
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. · Contribute to the development, optimization, and validation of novel experimental methods and research models. · Maintain accurate and comprehensive experimental records and ensure