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for teaching, the teaching/learning process, and for individual students. Applying your skills and experience to your assigned teaching schedule. Participating in and contributing to assessment activities
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of causal reasoning tools, including causal inference, counterfactual analysis, causal discovery. Development of deep learning methods on computer vision. Job Requirements: Preferably PhD in Computer
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of causal reasoning tools, including causal inference, counterfactual analysis, causal discovery. Development of deep learning methods on computer vision. Job Requirements: Preferably Master in Computer
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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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teaching, tutorial and laboratory as may reasonably be assigned by the Principal Person Specification Capability to carry out research more than one of the following areas: AI and Deep Learning in Healthcare
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nanoparticles. The successful candidate will also learn cutting edge deep-sequencing approaches to evaluate off-target editing within the genome. They will have the opportunity to participate in meetings
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turbine engines. Successful candidates will have a PhD or equivalent in a relevant discipline and experience in the development of machine/deep learning (ML/DL) methods for engineering and will use
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techniques, methods, and research, especially deep learning literature, and how these methods apply to our use cases Ability to manage multiple projects and assignments with a high level of autonomy and
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Want a career with a deep sense of purpose while working with the support of a highly skilled, dedicated and compassionate interdisciplinary team? Utilize and learn skilled nursing care and see the
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inference [1] modeling by combining probabilistic reasoning [2] and deep learning models [3]. The objective is thus to have a model capable to reason under uncertainty. Especially, the postdoc will research