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Field
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; multi-modal scene sensing and interpretation; pre-harvest fruit quality assessment; and perception algorithms for autonomous crop harvesting. We are particularly interested in applicants with experience
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at the weekly seminars. Present results internally and at international venues; Qualifications PhD in Applied Mathematics or Computer Science (at the time of appointment), with strong research record in privacy
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• A strong foundation in mathematics, particularly in probability and optimization. • A PhD degree (or close to PhD completion) in engineering or management science degree, related
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2029. This role is eligible for hybrid working with a minimum of 60% on site. If you need any reasonable adjustments to apply, contact About you You must have: A PhD (awarded or near completion) in
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system model new module integration, scenario simulations, and prognostics analyses Physics-informed deep learning/hybrid modeling/reasoning AI algorithm development and optimization Job Requirements: A
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journals and conferences. Required Qualifications • Ph.D. in Electrical and Computer Engineering, Computer Science, or a related field. • PhD must be awarded no more than four years prior to the effective
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across AI, incorporating insights from algorithm development, systems engineering and architecture, human psychology, sociology, law, science and technology studies, economics, and policy studies. Faculty
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on developing new generative modeling approaches, scalable training algorithms, and foundation model technologies. The role is suited for candidates with a strong machine learning background who are excited
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aligned with the aims of the Terascale project. Develop and apply suitable methodologies for research for AI for science and catalyst discovery. Design, implement, and evaluate novel models, algorithms
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-structures. Develop numerical algorithms and computer codes that can be used to model nonlinear optical effects pertaining to light-matter interaction. Validate the theoretical models and software tools by