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. This interdisciplinary position sits at the intersection of robotics, machine learning, and sustainable chemistry. You will join a vibrant research environment at the University of Liverpool, building upon our team's
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candidate will be expected to work onsite as of their effective start date. This position is for a post-PhD trainee preparing for a research scientist career path. The planned position will provide a
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. The ideal candidate should have a strong background in artificial intelligence and machine learning, with demonstrated experience in developing and training neural networks for predictive modeling. Position
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gravitational effects on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning, quantum computing
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collaborators. Requirements: Applicants should have a PhD in Computer Engineering, Computer Science, or a related field. Extensive and sound knowledge of ML, AI, DNN, LLMs/VLMs, Multimodal LLMs, RAG, Agentic
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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | about 2 months ago
on LazySlide ( et al Nature Methods ), our scalable software foundation, and our deep learning framework for age prediction (Abila et al., Nature Medicine, in press) to engineer a body-scale machine learning
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, condensed matter physics, or a related field, with experience in first-principles calculations and/or machine learning for materials research being highly desirable. For additional information about this
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should have the following qualifications: Ph. D. degree in data science, electrical engineering, computer engineering, computer science, mathematical engineering, or similar. Proven track record in
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science, machine learning or a related field. Strong experience working with clinical, biomedical, genetic, electronic health record, or health administrative data. Experience with large language models
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years of experience post receiving their PhD). A strong preference is for individuals with (a) computer science or computer engineering degrees with previous experience in natural language processing