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Field
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the intersection of programming languages and artificial intelligence (PL+AI), in particular verification and large language models. Our main goal is to create a PL+AI system that is the best at verified program
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. The faculty has research environments in popular music, classical music, visual arts, and performing arts, with two PhD programs: PhD program in Artistic Research and PhD program in Fine Arts . This position
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Department of Popular Music. The faculty has research environments in popular music, classical music, visual arts, and performing arts, with two PhD programs: PhD Program in Artistic Research and PhD Program
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, probabilistic graphical models, physics/dynamical systems. Qualifications: The candidate is expected to hold (or be about to complete) a relevant PhD degree in Computer Science, Artificial Intelligence or another
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, visual arts, and performing arts, with two PhD programs: PhD program in Artistic Research and PhD program in Fine Arts . This position is linked to the PhD program in Fine Arts. Responsibilities
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arts, with two PhD programs: PhD Program in Artistic Research and PhD Program in Fine Arts . This position is linked to the PhD program in Arts. Responsibilites The position is part of MishMash – Center
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. This position focuses on the development and application of large language models (LLMs) for advancing food informatics, food bioactives research, and sustainable food innovation. The selected fellow
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manuscripts to publish at the top-tier venues Stay abreast of the cutting-edge developments in AI research--particularly pertaining Large language models Multimodality Model alignment and safety Diffusion and
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research proposals and reports. Job Requirements Possess a PhD degree obtained in a related discipline (transportation engineering, operations research, computer engineering/science, or related disciplines
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an opportunity for academic development through a PhD education leading to a doctoral degree. The hired candidate will be admitted to the PhD program in Science and Technology, specialisation in Risk Management